EP2315914B1 - Methods and apparatus to form a well - Google Patents
Methods and apparatus to form a well Download PDFInfo
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- EP2315914B1 EP2315914B1 EP09751070.5A EP09751070A EP2315914B1 EP 2315914 B1 EP2315914 B1 EP 2315914B1 EP 09751070 A EP09751070 A EP 09751070A EP 2315914 B1 EP2315914 B1 EP 2315914B1
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Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B7/00—Special methods or apparatus for drilling
- E21B7/04—Directional drilling
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
- E21B47/02—Determining slope or direction
- E21B47/022—Determining slope or direction of the borehole, e.g. using geomagnetism
Definitions
- Drilling, completion, and production of hydrocarbon reservoir wells involve drilling boreholes that intersect or traverse hydrocarbon-bearing deposits.
- drilling rigs at the surface are used to drill boreholes to reach the location of subsurface oil or gas deposits and establish fluid communication between the deposits and the surface via the borehole.
- Downhole drilling equipment may be directed or steered to the oil or gas deposits using directional drilling techniques.
- Evaluations of subterranean formations penetrated by the borehole can be used to identify subsurface formations having characteristics indicative of good production/drainage.
- the drilling equipment may be removed from the borehole and a wireline tool can be deployed into the borehole to sample and/or test one or more formation fluids at various stations or positions of the wireline tool.
- the drilling equipment of a drill string may include a downhole tool to sample and/or test the fluids of the surrounding subterranean formation. The sampling may be accomplished using formation testing tools that retrieve the formation fluids at desired borehole positions or stations and/or test the retrieved fluids in situ.
- formation fluids may be collected in one or more chambers associated with the downhole tool.
- the fluid samples obtained from the subterranean formations can be brought to the surface and evaluated to determine the properties of the fluids and the condition of the subterranean formations, and thereby locate exploitable oil and/or gas deposits.
- fluid composition data can also be represented by raw spectroscopic data such as, for example, a spectrum of mass fragments as used in mass spectrometry, a spectrum of optical densities, fluorescence data, refractive index data, Nuclear Magnetic Resonance (NMR) data, and dielectric spectrum data.
- fluid properties may additionally or alternatively be represented or described using parameters or sets of parameters used in equations that describe characteristics of a fluid such as, for example, sets of parameters used in equations of state (EoS) or coefficients used, for example, as part of neural network methods and/or radial basis functions which are fit to entries contained in one or more fluid property databases.
- EoS equations of state
- the requisite non-collinear condition is achieved by causing either or both of an upper or a lower stabilizer(s) to apply an eccentric force or displacement in a direction that is preferentially orientated with respect to the direction of hole propagation.
- an upper or a lower stabilizer(s) to apply an eccentric force or displacement in a direction that is preferentially orientated with respect to the direction of hole propagation.
- this may be achieved, including non-rotating (with respect to the hole) eccentric stabilizers (displacement based approaches) and eccentric actuators that apply force to the drill bit in the desired steering direction.
- steering is achieved by creating non co-linearity between the drill bit 2 and at least two other touch points.
- the MWD tool 124 is also used to perform two-way telemetry between the surface system 120 and downhole components of the BHA 116.
- the MWD tool 124 can be used to receive commands from the surface system 120 related to collecting fluid samples from the well 102 and/or measuring the fluid samples.
- the seismic VISIONTM seismic while drilling tool provided by Schlumberger Technology Corporation
- an acoustic imaging tool e.g., the seismic VISIONTM seismic while drilling tool provided by Schlumberger Technology Corporation
- a resistivity imaging tool e.g., the geoVISIONTM resistivity imaging tool and the PeriScope 15 TM deep-reading resistivity tool both provided by Schlumberger Technology Corporation.
- the sampling while drilling tool 142 is provided with a data processor 214.
- the data processor 214 is configured to determine fluid properties (e.g., fluid elements and/or composition, GOR, saturation pressures, formation mobility, fluid color, asphaltene or wax concentration levels, pressure, temperature, density, viscosity, compressibility, EoS parameters, thermal and chemical properties, etc%) of formation fluid samples based on the measurement data collected by the spectrometer 204 and/or the one or more sensors 205.
- fluid properties e.g., fluid elements and/or composition, GOR, saturation pressures, formation mobility, fluid color, asphaltene or wax concentration levels, pressure, temperature, density, viscosity, compressibility, EoS parameters, thermal and chemical properties, etc.
- the fluid simulator 312 can be used to determine hydrocarbon chain length distribution along the entire well.
- the PVT ProTM EoS simulation tool developed and sold by Schlumberger Technology Corporation can be used to implement the fluid EoS simulator of the fluid simulator 312, or the PVTiTM EoS tool developed and sold by Schlumberger Technology Corporation can be used to implement the fluid simulator 312.
- the example apparatus 300 is provided with a reservoir simulator 314 which generates fluid composition data for a distribution across an entire reservoir.
- the reservoir simulator 314 can arrange the fluid composition data to generate a fluid composition distribution for that reservoir.
- the reservoir simulator 314 is configured to use the features of the geological model stored in the reservoir geological model database 302 to populate the entire simulated reservoir in an empirical manner. That is, as the geological model data improves or more geological model data is acquired using, for example, fluid sample measurements or other types of measurements, the reservoir simulator 314 can update the fluid composition distribution or fluid map of the reservoir R.
- OD(h) is the optical density or color of the oil at a height ( h ) induced by the asphaltene content
- V is the volume of the asphaltene colloidal particle (found to be ⁇ 16 ⁇ for black oils)
- ⁇ is the density contrast between asphaltene and the bulk oil
- g is the Earth's gravitational constant
- k is the Boltzmann's constant
- T is the temperature.
- a semi-empirical methodology could alternatively be employed to describe the asphaltene concentration in those compressible oils.
- the mud gas logging tool 138 can monitor one or more molecular concentration(s) (e.g. methane concentration, ethane concentration, carbon dioxide concentration, concentration of a fluid injected in the reservoir etc%) extracted from the drilling mud samples after accounting for concentrations initially present in the drilling fluid 26 leaving the drill bit 106.
- the mud gas logging tool 138 may also be used to monitor one or more concentration(s) of isotopes (e.g. the isotopes of carbon, 12 C, 13 C, etc...) associated with gases extracted from the drilling mud samples after accounting for concentrations initially present in the drilling fluid 26 leaving the drill bit 106.
- the surface logging and control system 120 After the surface logging and control system 120 adjusts the mud gas logging calibration (block 419) or if the surface logging and control system 120 determines that it should not adjust the mud gas logging calibration data (block 418) or if a sidewall sample measurement is not performed (block 414), the surface logging and control system 120 compares at least one of the measured fluid composition data (and its composition uncertainty) derived from the measurements acquired by the mud gas logging tool 138 at block 412 and the measured fluid composition data (and its composition uncertainty) derived from the measurements acquired during the sidewall sampling operation of block 416 with the predicted and/or desired (or target) composition data (and its composition uncertainty) (block 420).
- Fluid sample composition data determined at block 608 is then compared to the predicted and/or desired (or target) (e.g., sufficiently low) log data determined at block 604 (block 610).
- the comparison is used along with pressure measurements for a proposed well to determine if the pressure in the proposed well is sufficient for an injected gas to be miscible with in-situ oil and if the gas injection scheme is effective in contacting and mobilizing the remaining oil in the well formation F ( FIG. 1B ).
- each comparison may indicate a different result such that some portions of the proposed well have sufficient pressure while others may not.
- the comparison of block 610 will also indicate what changes should be made to reservoir fluid map data in the reservoir fluid map database 316 to reflect the latest data acquired at block 608.
- the sampling while drilling tool 142 draws a formation fluid sample (block 802) and analyzes the fluid sample (block 804).
- the sampling while drilling tool 142 can draw the formation fluid sample via the probe 144 and analyze the fluid sample using the spectrometer 204 and/or the one or more additional sensor(s) 205.
- the measurements acquired using the sampling while drilling tool 142 include measures of optical absorption in the visible range and pressure measurements. Asphaltene typically causes an optical absorption that varies in the visible light range exponentially with the light frequency.
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- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Geology (AREA)
- Mining & Mineral Resources (AREA)
- Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Fluid Mechanics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Geophysics (AREA)
- Earth Drilling (AREA)
- External Artificial Organs (AREA)
Description
- The present disclosure relates generally to measuring formation fluids and, more particularly, to methods and apparatus to form a well.
- Drilling, completion, and production of hydrocarbon reservoir wells involve drilling boreholes that intersect or traverse hydrocarbon-bearing deposits. Typically, drilling rigs at the surface are used to drill boreholes to reach the location of subsurface oil or gas deposits and establish fluid communication between the deposits and the surface via the borehole. Downhole drilling equipment may be directed or steered to the oil or gas deposits using directional drilling techniques.
- Evaluations of subterranean formations penetrated by the borehole can be used to identify subsurface formations having characteristics indicative of good production/drainage. To perform such evaluations, the drilling equipment may be removed from the borehole and a wireline tool can be deployed into the borehole to sample and/or test one or more formation fluids at various stations or positions of the wireline tool. Alternatively, the drilling equipment of a drill string may include a downhole tool to sample and/or test the fluids of the surrounding subterranean formation. The sampling may be accomplished using formation testing tools that retrieve the formation fluids at desired borehole positions or stations and/or test the retrieved fluids in situ. Alternatively, formation fluids may be collected in one or more chambers associated with the downhole tool. The fluid samples obtained from the subterranean formations can be brought to the surface and evaluated to determine the properties of the fluids and the condition of the subterranean formations, and thereby locate exploitable oil and/or gas deposits.
- Formation fluid test data can be used to design completion equipment, or to plan trajectories of successive wells in the same reservoir or to monitor the reservoir over time in order to manage production and recovery, etc...
- Document
US 2008/040086 discloses methods and apparatus by which formation fluid data based on measurements taken downhole under natural conditions is utilized to help identify reservoir compartments. A geological model of the reservoir including expected pressure and temperature conditions is integrated with a predicted fluid model fitted to measured composition and PVT data on reservoir fluid samples or representative analog. Synthetic downhole fluid analysis (DFA) logs created from the predictive fluid model can be displayed along the proposed borehole trajectory by geological modeling software prior to data acquisition. During a downhole fluid sampling operation, actual measurements can be displayed next to the predicted logs. If agreement exists between the predicted and measured fluid samples, the geologic and fluid models are validated. However, if there is a discrepancy between the predicted and measured fluid samples, the geological model and the fluid model need to be re-analyzed, e.g., to identify reservoir fluid compartments. A quantitative comparative analysis of the sampled fluids can be performed against other samples in the same borehole or in different boreholes in the field or region to calculate the statistical similarity of the fluids, and thus the possible connectivity between two or more reservoir regions. - Document
US 2006/155474 discloses methods and systems for downhole analysis of formation fluids by deriving fluid properties and associated uncertainty in the predicted fluid properties based on downhole data, and generating answer products of interest based on differences in the fluid properties. Measured data are used to compute levels of contamination in downhole fluids using an oil-base mud contamination monitoring (OCM) algorithm. Fluid properties are predicted for the fluids and uncertainties in predicted fluid properties are derived. A statistical framework is provided for comparing the fluids to generate, in real-time, robust answer products relating to the formation fluids and reservoirs thereof. Systematic errors in measured data are reduced or eliminated by preferred sampling procedures. - According to an aspect of the present invention, there is provided a method to form a well having the features of
claim 1 below. - Optional features are set out in the dependent claims below.
- According to another aspect the present invention, there is also provided a drilling system having the features of claim 9 below.
- Optional features are set out in the dependent claims below..
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FIG. 1A is an elevational view of a wellsite system that may be used to implement the example methods and apparatus described herein. -
FIG. 1B is an elevational view of another wellsite system that may be used to implement the example methods and apparatus described herein. -
FIG. 2 is an example block diagram of a sampling while drilling tool of the drill string ofFIG. 1B . -
FIG. 3A depicts a block diagram of an example apparatus that may be used to analyze well data to control a drill string to form a well. -
FIG. 3B depicts a portion of the example apparatus ofFIG. 3A that can be used to detect and account for fluid compositional variations. -
FIGS. 4A and4B depict a flowchart of an example method that may be used to implement the example apparatus ofFIG. 3 to control the well trajectory of a well. -
FIG. 5 is a flowchart of an example method that may be used to determine whether to stop drilling operations based on real-time well production simulations. -
FIG. 6 is a flowchart of an example method that may be used to place a well in a reservoir containing injected fluid. -
FIG. 7 is a flowchart of an example method that may be used to adjust well trajectories to plan a well in a compartmentalized reservoir. -
FIG. 8 is a flowchart of an example method that may be used to steer a well trajectory based on asphaltene precipitation onset pressure. -
FIG. 9 is a flowchart of an example method that may be used to control the trajectory of a well to maintain the well trajectory below a gas-oil contact in an oil zone. - The methods of
fig 5 to 9 are not claimed. - Certain examples are shown in the above-identified figures and described in detail below. In describing these examples, like or identical reference numbers are used to identify common or similar elements. The figures are not necessarily to scale and certain features and certain views of the figures may be shown exaggerated in scale or in schematic for clarity and/or conciseness.
- The example methods and apparatus described herein can be used to determine a well trajectory based on real-time or substantially real-time downhole measurements of reservoir fluid properties. The example methods and apparatus can be used during exploration and appraisal phases of a reservoir. For example, the example methods and apparatus can be used to steer a drill string to form the well trajectory so that useful information about the fluid distribution in the reservoir can be measured. Thus, in some example implementations, the well trajectory can be adjusted to optimize reservoir characterization.
- The example methods and apparatus described herein can also be used during a development phase of a reservoir. For example, the example methods and apparatus can be used to steer a drill string so that a producing well engages hydrocarbon accumulations of sufficient economical value. Alternatively, the example methods and apparatus can be used to steer a drill string so that an injection well (e.g. a gas injection well) engages particular flow units in the reservoir. Thus, in some example implementations, the well trajectory can be adjusted to optimize the reservoir drainage/production, either directly (as in the case of a producing well) or indirectly (as in the case of an injection well).
- The example methods and apparatus described herein can be implemented to use in-situ measurements indicative of formation fluid properties and/or a reservoir fluid property map. A formation fluid property can be determined by measuring a property of downhole fluid in or extracted from formation rock surrounding the borehole of a well. A reservoir extends beyond the immediate formation rock surrounding the borehole of a well. A reservoir fluid property map can be determined from the measured fluid property using various extrapolation techniques further detailed herein.
- In some example implementations that use formation fluid properties to control a drill string to form a well trajectory, the example methods and apparatus described herein are configured to determine a reservoir fluid property map on a portion of a reservoir; convey at least one fluid property sensor into a reservoir well using, for example, a drill string; perform in-situ measurements using the sensor indicative of a formation fluid property; compare the in-situ measurements with the property map; and adjust a well trajectory based on the comparison. In such example implementations, the example methods and apparatus may also be configured to determine a reservoir fluid property uncertainty map on at least the same portion of the reservoir; determine the uncertainty associated with the in-situ measurements performed by the sensor; and compare the in-situ measurement uncertainties with the property map and/or its associated uncertainty map.
- In some example implementations that use reservoir fluid properties to control a drill string to form a well trajectory, the example methods and apparatus described herein are configured to convey at least one fluid property sensor into a reservoir well using, for example, a drill string; perform at least one in-situ measurement using the sensor indicative of a reservoir fluid property; determine a reservoir fluid property map on a portion of the reservoir based on the in-situ measurement; and adjust a well trajectory based on the determined property map. In such example implementations, the example methods and apparatus may also be configured to determine a reservoir fluid property uncertainty map associated with the at least one measurement and adjust a well trajectory based on the property map and/or the uncertainty indicated by the property uncertainty map.
- In the illustrated examples described herein, the formation and/or reservoir fluid properties include properties that are related (e.g., first-order related) to the reservoir fluid composition. In particular, the fluid properties can be one or more properties (e.g., in combination) of fluid compositions, and can relate to either partial or a full description of the composition, constituent isotope ratios, gas-liquid ratios, etc. Fluid composition data can alternatively be described with thermo-physical data such as, for example, fluid bulk density, saturation pressures, viscosity, fluid acoustic impedance (i.e. the square root of the product of the fluid compressibility by the fluid density), and fluid compressibility at a given pressure and temperature. In addition, fluid composition data can also be represented by raw spectroscopic data such as, for example, a spectrum of mass fragments as used in mass spectrometry, a spectrum of optical densities, fluorescence data, refractive index data, Nuclear Magnetic Resonance (NMR) data, and dielectric spectrum data. In some example implementations, fluid properties may additionally or alternatively be represented or described using parameters or sets of parameters used in equations that describe characteristics of a fluid such as, for example, sets of parameters used in equations of state (EoS) or coefficients used, for example, as part of neural network methods and/or radial basis functions which are fit to entries contained in one or more fluid property databases.
- Although the example methods and apparatus described herein can be used to adjust a well trajectory by adjusting the direction, travel, and path of a well trajectory, adjusting a well trajectory as described herein may also include terminating all further planned drilling operations. Such may be the case where in-situ measurements indicate that it would not be productive to continue drilling a particular well in a particular reservoir or at a particular position in the reservoir.
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FIG. 1A illustrates a wellsite system in which the example methods and apparatus described herein can be employed. The wellsite can be onshore or offshore. In this example system, a borehole 11 is formed in subsurface formations by rotary drilling in a manner that is well known. Example implementations of the example methods and apparatus can also use directional drilling, as will be described hereinafter. - A
drill string 12 is suspended within the borehole 11 and has abottom hole assembly 1 which includes adrill bit 2 at its lower end. The surface system includes platform andderrick assembly 10 positioned over the borehole 11, theassembly 10 including a rotary table 16, akelly 17, ahook 18, and a rotary swivel 19. Thedrill string 12 is rotated by the rotary table 16, energized by means not shown, which engages thekelly 17 at the upper end of thedrill string 12. Thedrill string 12 is suspended from thehook 18, attached to a traveling block (not shown), through thekelly 17 and the rotary swivel 19, which permits rotation of thedrill string 12 relative to thehook 18. As is well known, a top drive system could alternatively be used. - In the illustrated example implementation, the surface system further includes drilling fluid or
mud 26 stored in apit 27 formed at the well site. Apump 29 delivers thedrilling fluid 26 to the interior of thedrill string 12 via a port in the swivel 19, causing the drilling fluid to flow downwardly through thedrill string 12 as indicated by the directional arrow 8. The drilling fluid exits thedrill string 12 via ports in thedrill bit 2, and then circulates upwardly through the annulus region between the outside of thedrill string 12 and the wall of the borehole, as indicated by the directional arrows 9. In this well known manner, thedrilling fluid 26 lubricates thedrill bit 2 and carries formation cuttings up to the surface as it is returned to thepit 27 for recirculation. - The
bottom hole assembly 1 of the illustrated example implementation includes a logging-while-drilling (LWD)module 4, a measurement-while-drilling (MWD)module 5, a rotary-steerable system and motor 6 (e.g., a directional drilling subsystem), and thedrill bit 2. - The
LWD module 4 is housed in a special type of drill collar, as is known in the art, and can contain one or a plurality of known types of logging tools. It will also be understood that more than one LWD and/or MWD module can be employed, e.g. as represented at 7. (References, throughout, to a module at the position of 5 can alternatively mean a module at the position of 7 as well.) TheLWD module 4 includes capabilities for measuring, processing, and storing information, as well as for communicating with theMWD module 5. In the present embodiment, theLWD module 4 includes a fluid property sensor. - The
MWD module 5 is also housed in a special type of drill collar, as is known in the art, and can contain one or more devices for measuring characteristics of the drill string and drill bit. TheMWD module 5 further includes an apparatus (not shown) for generating electrical power to the downhole system. This may typically include a mud turbine generator powered by the flow of the drilling fluid, it being understood that other power and/or battery systems may be employed. In the present embodiment, theMWD module 5 includes one or more of the following types of measuring devices: a weight-on-bit measuring device, a torque measuring device, a vibration measuring device, a shock measuring device, a stick slip measuring device, a direction measuring device, and/or an inclination measuring device. TheMWD module 5 further includes capabilities for communicating with surface equipment. - A particularly advantageous use of the example methods and apparatus described herein is in conjunction with controlled steering or "directional drilling" using the rotary-
steerable subsystem 6. Directional drilling is the intentional deviation of the wellbore from the path it would naturally take. In other words, directional drilling is the steering of the drill string so that it travels in a desired direction. Directional drilling comprises geometrical steering, in which the drill bit is typically steered along a pre-determined path in an Earth formation, and geological steering, in which the drill bit is typically steered relative to geological features of the Earth formation. Directional drilling is, for example, advantageous in offshore drilling because it enables many wells to be drilled from a single platform. Directional drilling also enables horizontal drilling through a reservoir. Horizontal drilling enables a longer length of the wellbore to traverse the reservoir, which increases the production rate from the well. A directional drilling system may also be used in vertical drilling operations as well. Often thedrill bit 2 will veer off of a planned drilling trajectory because of the unpredictable nature of the formations being penetrated or the varying forces that thedrill bit 2 experiences. When such a deviation occurs, a directional drilling system (e.g., the rotary-steerable subsystem 6) may be used to put thedrill bit 2 back on course. - A known method of directional drilling includes the use of a rotary steerable system ("RSS"). In an RSS, the
drill string 12 is rotated from the surface, and downhole devices cause the drill bit-2 to drill in the desired direction. Rotating thedrill string 12 greatly reduces the occurrences of thedrill string 12 getting hung up or stuck during drilling. Rotary steerable drilling systems for drilling deviated boreholes into the earth may be generally classified as either "point-the-bit" systems or "push-the-bit" systems. In the point-the-bit system, the axis of rotation of thedrill bit 2 is deviated from the local axis of thebottom hole assembly 1 in the general direction of the new hole. The hole is propagated in accordance with the customary three point geometry defined by upper and lower stabilizer touch points and thedrill bit 2. The angle of deviation of thedrill bit 2 axis coupled with a finite distance between thedrill bit 2 and a lower stabilizer results in the non-collinear condition required for a curve to be generated. There are many ways in which this may be achieved including a fixed bend at a point in thebottom hole assembly 1 close to the lower stabilizer or a flexure of thedrill bit 2 drive shaft distributed between an upper and the lower stabilizer. In its idealized form, thedrill bit 2 is not required to cut sideways because the bit axis is continually rotated in the direction of the curved hole. Examples of point-the-bit type rotary steerable systems, and how they operate are described inU.S. Patent Application Publication Nos. 2002/0011359 ;2001/0052428 andU.S. Patent Nos. 6,394,193 ;6,364,034 ;6,244,361 ;6,158,529 ;6,092,610 ; and5,113,953 , all of which are hereby incorporated herein by reference in their entireties. - In the push-the-bit rotary steerable system there is usually no specially identified mechanism to deviate the bit axis from the local bottom hole assembly axis; instead, the requisite non-collinear condition is achieved by causing either or both of an upper or a lower stabilizer(s) to apply an eccentric force or displacement in a direction that is preferentially orientated with respect to the direction of hole propagation. Again, there are many ways in which this may be achieved, including non-rotating (with respect to the hole) eccentric stabilizers (displacement based approaches) and eccentric actuators that apply force to the drill bit in the desired steering direction. Again, steering is achieved by creating non co-linearity between the
drill bit 2 and at least two other touch points. In some instances, thedrill bit 2 is required to cut side ways to generate a curved hole. Examples of push-the-bit type rotary steerable systems, and how they operate are described inU.S. Patent Nos. 5,265,682 ;5,553,678 ;5,803,185 ;6,089,332 ;5,695,015 ;5,685,379 ;5,706,905 ;5,553,679 ;5,673,763 ;5,520,255 ;5,603,385 ;5,582,259 ;5,778,992 ;5,971,085 , all of which are hereby incorporated herein by reference in their entireties. -
FIG. 1B is an elevational view of another wellsite system that may be used to implement the example methods and apparatus described herein. In the illustrated example, a platform andderrick assembly 100 are positioned over a well 102 (e.g., a wellbore or borehole) penetrating a subsurface formation F in a reservoir R. Although the platform andderrick assembly 100 are shown as a land-based rig, the example methods and apparatus described herein are not limited for use with land-based rigs. Adrill string 104 is suspended within the well 102 and includes adrill bit 106 at its lower end. Thedrill string 104 is rotated by a rotary table 108, energized by means not shown, which engages akelly 110 at the upper end of thedrill string 104. Thedrill string 104 is suspended from ahook 112, attached to a traveling block (not shown), through thekelly 110 and arotary swivel 114, which permits rotation of thedrill string 104 relative to thehook 112. In the illustrated example, the well 102 is formed using directional drilling. - The
drill string 104 further includes a bottom hole assembly (BHA) 116 coupled to thedrill bit 106. TheBHA 116 includes adirectional drilling subassembly 118 to adjust the drilling direction of thedrill bit 106 based on control signals received from, for example, a surface logging andcontrol system 120. TheBHA 116 includes capabilities for measuring, processing, and storing information, as well as communicating with surface equipment. In the illustrated example, theBHA 116 includes, among other things, a telemetry and measurement while drilling (MWD) tool 124 (i.e., a survey tool). TheMWD tool 124 is configured to send direction and inclination data to the surface and track the actual well trajectory of thewell 102. TheMWD tool 124 is also used to perform two-way telemetry between thesurface system 120 and downhole components of theBHA 116. For example, theMWD tool 124 can be used to receive commands from thesurface system 120 related to collecting fluid samples from the well 102 and/or measuring the fluid samples. - In the illustrated example, the
BHA 116 is provided with a logging while drilling (LWD) tool 126 (i.e., a formation evaluation tool). Although oneLWD tool 126 is shown, in other example implementations, theBHA 116 can be provided with any number of LWD tools. TheLWD tool 126 is used to obtain formation evaluation logs of the well 102 and improve the petrophysical knowledge of the reservoir R while the well 102 is being drilled. TheLWD tool 126 and any other LWD tool provided to theBHA 116 may be any combination of, for example, a Nuclear Magnetic Resonance (NMR) tool (e.g., the pro VISION™ nuclear magnetic resonance while drilling tool provided by Schlumberger Technology Corporation), a nuclear spectroscopy tool for obtaining lithology and porosity information (e.g., the EcoScope™ formation evaluation tool provided by Schlumberger Technology Corporation), a sonic tool (e.g. the sonic VISION™ sonic while drilling tool provided by Schlumberger Technology Corporation), a seismic tool (e.g. the seismic VISION™ seismic while drilling tool provided by Schlumberger Technology Corporation), an acoustic imaging tool, and/or a resistivity imaging tool (e.g., the geoVISION™ resistivity imaging tool and the PeriScope 15 ™ deep-reading resistivity tool both provided by Schlumberger Technology Corporation). - To communicate measurement information associated with the formation F surrounding the well 102 and the reservoir R to the
surface system 120 and to receive direction drilling control signals, thebottom hole assembly 116 is provided with atelemetry system 128 that may include, preferably but not necessarily, wired pipes (not shown). A telemetry system that may be used to implement theexample telemetry system 128 is described in detail inU.S. patent application serial no. 11/498,845, filed on August 3, 2006 wireless data transceiver 150 can be coupled to thedrill string 104 as shown inFIG. 1B to exchange data between the surfacelogging control system 120 and theBHA 116. However, other telemetry systems, such as two ways mud pulse telemetry systems, may alternatively or additionally be used. - In the illustrated example, the
BHA 116 includes a downhole mudgas logging tool 138. The downhole mudgas logging tool 138 has aninlet 140 for receiving fluids from theannulus 136. A portion of the fluids received in the downhole mudgas logging tool 138 via theinlet 140 includes formation fluid that has been released into the drilling mud as the formation rock was crushed during drilling. The mudgas logging tool 138 is capable of separating volatiles (e.g. hydrocarbons of low molecular weight) from the received fluids and in the process generating gas using, for example, a volume expansion and/or heating process. In the illustrated example, the downhole mudgas logging tool 138 is provided with agas sensor 141 to measure composition data for the separated gases. Data related to the composition of the separated gases may be analyzed using any suitable composition analysis device or methodology, including, for example, a mass spectrometer or a gas chromatographer. In addition, downhole mud gas logging preferably distinguishes between "background" concentration of hydrocarbon in the mud and "incoming" concentration originating from the rock being drilled by periodically measuring and accounting for "background" concentration of hydrocarbon in the mud. - Although many types of hydrocarbons and hydrocarbon structures exist in a reservoir, mud gas logging may only measure a subset of data (e.g., data indicative of the most volatile components contained in the formation fluid) that can otherwise be acquired using other techniques such as, for example, sidewall sampling. Indeed, mud gas logging looks only at a subset of the hydrocarbons and gases usually encountered in Earth formations (e.g., volatile hydrocarbons, carbon dioxide, hydrogen sulphide, nitrogen, etc.) and typically excludes those components that are trapped in the drill cuttings or are present in the
drilling fluid 26 but are not easily volatilized (e.g., those components which have molecular weights at least as large as those of the components of synthetic oil-based muds). However, in contrast to sidewall sampling which involves halting drilling operations at least momentarily, mud gas logging involves nearly continuous data acquisition along a well as the well is being drilled without needing to stop the drill string. In this way, the mud gas logging data can be used to determine partial but almost continuous representations of a reservoir fluid while a well is being drilled. Further, based on the hydrocarbon concentration measurements (e.g., a ratio of concentration of hydrocarbon types), mud gas logging can be used to determine changes in the type of formation fluids that are expected to be found as soon as a new formation is being drilled. - To acquire relatively quantitative mud gas logging data, the mud
gas logging tool 138 is operated in connection with calibration data. The mud gas logging calibration data is generated based on known characteristics or fluid properties of a well. In the illustrated examples described herein, the mud gas logging calibration data is determined, at least in part, based on sidewall sampling data (e.g., sidewall sample measurements acquired by the sampling whiledrilling tool 142 described below). As discussed below in connection with the example process ofFIGS. 4A and4B , the mud gas logging calibration data can be checked against actual fluid sample measurements acquired using sidewall sample measurements to determine whether the mud gas logging calibration should be adjusted. Hydrocarbon measurements acquired using a sampling while drilling tool represent snapshots of the fluid in the formation F from different locations. The hydrocarbon measurements are then used to determine what type of fluid is expected to be present in the formation. The sidewall sampling measurements then confirm whether the fluid type estimations made using the hydrocarbon data provided by the mudgas logging tool 138 are quantitatively correct or within an accuracy threshold. If so, the mud gas logging data is deemed to be correct (or does not require adjustment). Otherwise, the mud gas logging calibration data is adjusted to enable the mudgas logging tool 138 to generate mud gas logging data that is in agreement with the sidewall fluid sample measurements. - A downhole mud gas logging tool that may be used to implement the mud
gas logging tool 138 is describe inU.S. patent application serial no. 11/312,683, filed on December 19, 2005 gas logging tool 138. - In the illustrated example, the
bottom hole assembly 116 includes a sampling whiledrilling tool 142. The sampling whiledrilling tool 142 includes aprobe 144 to engage a surface of the well 102 to draw fluids from the reservoir R. In other example implementations, straddle packers (not shown) can additionally or alternatively be used to engage and isolate a portion of the surface of the well 102 to draw fluids from the reservoir R. - To determine sampling locations in the formation F, the sampling while
drilling tool 142 may be operated in connection with a continuous representation of a reservoir fluid along the well trajectory. In some example implementations, the continuous representations of a reservoir fluid along the well trajectory may be provided by data generated by the mudgas logging tool 142. For example, as described earlier, the mudgas logging tool 142 is capable of providing almost continuous representations of a reservoir fluid while a well is being drilled. Thus, based on a ratio of concentrations of hydrocarbon types measured by the mudgas logging tool 142, changes in the type of formation fluids that are expected to be found can be identified as soon as a new formation is being drilled. The location of such a change may be used to set the sampling tool probe in the suspected new formation. The sampling tool may then draw and analyze formation fluid from the new formation and provide a more complete description of the fluid in that formation. - An example detailed block diagram of the sampling while
drilling tool 142 is shown inFIG. 2 . In the illustrated example ofFIG. 2 , the sampling whiledrilling tool 142 is provided with apump 202 that draws fluids from the formation F into thetool 142. Thepump 202 can be controlled to withdraw sufficient fluid from the reservoir R so that contamination-free reservoir fluid properties can be estimated. That is, during an initial pumping phase, thepump 202 may draw a mixture of formation fluid and thedrilling fluid 26 that has invaded the formation F (see filtrate invadedzone 182 inFIG. 1B ), which is a contaminant in the formation fluid. After some time, the fluid drawn by thepump 202 has a reduced fraction of contaminants (e.g., invadeddrilling fluid 26 into the formation F), and measurements on pristine formation fluid can be performed. In some example implementations in which contaminants remain in the drawn formation fluid, computational filtering processes can be performed on the fluid sample measurement data to determine fluid properties of otherwise pristine fluid samples based on the contaminated samples. For example, to determine fluid optical density, a convex combination of optical densities from different fluid samples can be used to determine the fluid optical density of a pristine sample. To determine viscosity, a mixing rule such as, for example, a refinery (e.g., quarter power) formula or the Grundbarg-Nissan mixing rule can be applied to the measured fluid data. To determine fluid composition data, a subtraction or skimming method can be used in combination with an equation of state to determine the fluid composition data on a pristine sample. In the illustrated examples described herein, these types of corrections for contaminated fluid samples are performed in real time when well trajectory adjustments are determined in real time. - The sampling while
drilling tool 142 also includes one or more fluid sensors to measure the reservoir fluid drawn into thetool 142. In the illustrated example, the sampling whiledrilling tool 142 is provided with aspectrometer 204. Thespectrometer 204 may be implemented using, for example, a light absorption/fluorescence spectrometer, a NMR spectrometer, or a mass spectrometer. In other example implementations, the sampling whiledrilling tool 142 may be provided with a gas chromatographer (e.g., to perform one-dimensional or two-dimensional gas chromatography measurements) in addition to or instead of thespectrometer 204. In the illustrated example, the sampling whiledrilling tool 142 is also provided with one ormore sensors 205 to measure pressure/temperature, density/viscosity, and/or any other fluid properties. The sampling whiledrilling tool 142 may optionally include one or more fluid store(s) 206 connected to atool fluid bus 230, each store including one or more fluid sample chambers in which reservoir fluid recovered during sampling operations can be stored and brought to the surface for further analysis and/or confirmation of downhole analyses. - To store, analyze, process, and/or compress test and measurement data (or any other data acquired by the sampling while drilling tool 142), the sampling while
drilling tool 142 is provided with anelectronics system 208. In the illustrated example, theelectronics system 208 includes a controller 210 (e.g., a CPU and random access memory) to control operations of the sampling whiledrilling tool 142 and implement measurement routines (e.g., to control thespectrometer 204, etc.). To store machine accessible instructions that, when executed by thecontroller 210, cause thecontroller 210 to implement measurement processes or any other processes, theelectronics system 208 is provided with an electronic programmable read only memory (EPROM) 212. In the illustrated example, thecontroller 210 is configured to receive digital data from one or more sensors (e.g., thespectrometer 204 and the sensors 205) provided in the sampling whiledrilling tool 142. - To analyze measurement data, the sampling while
drilling tool 142 is provided with adata processor 214. In the illustrated example, thedata processor 214 is configured to determine fluid properties (e.g., fluid elements and/or composition, GOR, saturation pressures, formation mobility, fluid color, asphaltene or wax concentration levels, pressure, temperature, density, viscosity, compressibility, EoS parameters, thermal and chemical properties, etc...) of formation fluid samples based on the measurement data collected by thespectrometer 204 and/or the one ormore sensors 205. To store measurement data, analysis data, or any other kind of data, acquired, collected, and/or generated by the sampling whiledrilling tool 142 using, for example, thespectrometer 204, thecontroller 210, and/or thedata processor 214, theelectronics system 208 is provided with aflash memory 216. To communicate information when the sampling whiledrilling tool 142 is downhole, theelectronics system 208 is provided with amodem 218 that is communicatively coupled to anelectrical tool bus 220 communicatively coupled to the surface logging and control system 120 (FIG. 1B ). In the illustrated example, themodem 218 enables the surface logging andcontrol system 120 to retrieve measurement and/or analysis data stored in theflash memory 216. - In example implementations in which the
BHA 116 uses mud-pulse telemetry, theflash memory 216 preferably, but not necessarily, includes sufficient memory capacity to store all or essential segments of sensor measurement data and interpreted or analysis results computed by the sampling whiledrilling tool 142. In addition, thedata processor 214 preferably, but not necessarily, has sufficient processing power and the appropriate algorithms or data analysis routines to generate and store useable information based on the sensor measurement data. For example, thedata processor 214 can be configured to process the sensor measurement data to generate, for example, fluid composition data and the fluid constituent uncertainties, which may be compressed and relayed to thesurface system 120 so that real-time decisions can be made to determine a well trajectory of the well 102 (FIG. 1B ). In example implementations in which relatively high-bandwidth communications (e.g., wired communications via theelectrical tool bus 220 of the wired drill string 104 (FIG. 1B )) are available, themodem 218 can communicate the sensor measurement data to thesurface system 120, and thesurface system 120 can process and analyze the sensor measurement data. - Although the components of
FIG. 2 are shown and described above as being communicatively coupled and arranged in a particular configuration, the components of the sampling whiledrilling tool 142 can be communicatively coupled and/or arranged differently than depicted inFIG. 2 without departing from the scope of the present disclosure. For example, each of theprocessor 214 and the controller 210 (and/or processors in the surface logging andcontrol system 120 and thecomputer 146 ofFIG. 1B ) may be any suitable processor, processing unit, microprocessor, and/or controller. Theelectronics system 208 may be a multi-processor system (and/or multi-controller system) and, thus, may include one or more additional processors (and/or one or more additional controllers) that are identical or similar to the processor 214 (and/or controller 210). In addition, the example methods, apparatus, and systems described herein are not limited to a particular conveyance type but, instead, may be implemented in connection with different conveyance types including, for example, coiled tubing, wireline retrievable, wired-drill-pipe, and/or other conveyance means known in the industry. - Returning to
FIG. 1B , although theexample BHA 116 is shown as having the mudgas logging tool 138 and the sampling whiledrilling tool 142, in some example implementations, theBHA 116 may be provided with the mudgas logging tool 138 but not the sampling whiledrilling tool 142 or may be provided with the sampling whiledrilling tool 142 but not the mudgas logging tool 138. - As shown in
FIG. 1B , the surface logging andcontrol system 120 is communicatively coupled to acomputer 146 including a terminal display/input console 148 to enable an operator to monitor and interact with drilling operation associated with thedrill string 104. While thecomputer 146 and the terminal display/input console 148 are depicted as being located on the platform andderrick assembly 100, they can be remotely located from the platform andderrick assembly 100 and may communicate with thedrill string 104 via any communication link known in the art. -
FIG. 3A depicts a block diagram of anexample apparatus 300 that may be used to analyze well data to control a drill string (e.g., thedrill string 104 ofFIG. 1B ) to form a well (e.g., the well 102 ofFIG. 1B ). In particular, theexample apparatus 300 is configured to receive measurement and/or analysis data from theBHA 116 ofFIG. 1B , analyze the received data, and control a well trajectory of the well 102 by controlling the direction of drilling of theBHA 116. In some example implementations, theexample apparatus 300 can be used to adjust the well trajectory to optimize characterization of the reservoir R (FIG. 1B ). Theexample apparatus 300 can additionally or alternatively be used to adjust the well trajectory to optimize the drainage/production of the reservoir R. - The
example apparatus 300 may be implemented in theBHA 116, the surface logging andcontrol system 120, thesurface computer 146, or in any combination thereof using any desired combination of hardware, firmware, and/or software. For example, one or more integrated circuits, discrete semiconductor components, or passive electronic components may be used. Additionally or alternatively, some or all of the blocks of theexample apparatus 300, or parts thereof, may be implemented using instructions, code, and/or other software and/or firmware, etc. stored on a machine accessible medium that, when executed by, for example, a processor system (e.g., the example surface logging and control system 120 (FIG. 1B ), the computer 146 (FIG. 1B ), and/or theexample electronics system 208 ofFIG. 2 ), perform the operations represented in the flow diagrams ofFIGS. 4A ,4B , and5-9 . Although theexample apparatus 300 is described as having one of each block described below, theexample apparatus 300 may be provided with two or more of any block described below. In addition, some blocks may be disabled, omitted, or combined with other blocks. - Turning to
FIG. 3A in detail, theexample apparatus 300 includes a reservoirgeological model database 302 to store a reservoir geological model. Theexample apparatus 300 also includes a formationevaluation logs database 304 to store formation evaluation logs corresponding to wells previously drilled in the reservoir R and/or to a well (e.g., the well 102) currently being drilled. To store well trajectories (corresponding to previous wells and the current well), theexample apparatus 300 is provided with awell trajectory database 306. Theexample apparatus 300 is also provided with a fluidanalysis report database 308 to store fluid analysis reports corresponding to laboratory analyses of fluid samples collected in previous wells. The fluidanalysis report database 308 also stores in-situ fluid analysis data collected in previous wells and the current well. In addition, the fluidanalysis report database 308 may be used to store one or more sensor calibration(s) (e.g. mud gas logging calibration data). - Reservoir geological model data stored in the reservoir
geological model database 302 describes the locations of sedimentary layers, faults, etc. in the reservoir R (FIG. 1B ). The geological model can be generated using one or more seismic, electro-magnetic, gravity, or other surveys of the reservoir R, for example, prior to drilling a well (e.g., the well 102 ofFIG. 1B ). Preferably, but not necessarily, the reservoirgeological model database 302 also stores information relating to depositional sequences and reservoir structural information obtained from well image data such as, for example, gamma ray image data, density image data, and/or resistivity image data. - In some example implementations, formation evaluation logs of one well can include measurement data acquired in neighboring or offset wells. Formation evaluation log data stored in the formation
evaluation logs database 304 can be obtained while drilling (e.g. using thedrill string 104 ofFIG. 1B ) or after drilling (e.g., using a wireline tool) to determine the physical and chemical properties (e.g., petrophysical characteristics) of formations to better model subsurface fluid reservoirs. In the illustrated example, the formation evaluation logs include one or more of natural gamma ray data, resistivity data, porosity data, and density data. The data stored in the formation evaluation log database is preferably, but not necessarily, collected using tools which have at least the capabilities of tools referred to as "triple combo" tools that include, for example, a resistivity tool, a neutron porosity tool, and a nuclear density tool. - The formation evaluation logs may additionally or alternatively include spectroscopy data (e.g., nuclear spectroscopy data or NMR spectroscopy data). In the illustrated example, the formation evaluation logs preferably, but not necessarily, include formation pressure/temperature data points acquired in one or more offset wells formed in the reservoir R (
FIG. 1B ). If pressure data (from, for example, neighboring wells) is not available prior to drilling the current well (e.g., the well 102 ofFIG. 1B ), pressure data may be acquired while drilling the current well using, for example, the sampling while drilling tool 142 (FIGS. 1B-3B ). The formation evaluation logs may also store drilling events indicative of, for example, a mud loss, a mud weight, a weight on bit, a rate of penetration, etc. - Fluid analysis reports stored in the fluid
analysis report database 308 include data indicative of fluid compositions and thermo physical properties (e.g., temperature, pressure, volume, compressibility, density, viscosity, formation volume factor, gas-oil ratio, API gravity, phase envelope, thermal capacity, etc.) of fluids drawn from the reservoir R. The fluid analysis data can be used to determine how fluid properties vary along different depths of a formation and different portions of a reservoir. Fluid composition data can be measured in-situ or in a laboratory environment. In-situ fluid analysis (i.e., downhole fluid analysis) data can include data in the fluid analysis reports indicative of concentration levels of methane, (C1), ethane (C2), carbon dioxide (CO2), and water (H2O). In addition, the in-situ fluid analysis data can include concentration levels of fluid components such as, for example, the lumped group of propane, butane, and pentane (C3-5) and the lumped group of hydrocarbons with 6 or more carbons in their molecules (C6+). Gas-oil ratios of hydrocarbons can be derived from the fluid composition data. In addition, in-situ fluid analysis data can also include formation fluid pressure data, and fluid color related to, for example, concentration levels of asphaltene. In-situ fluid analysis data may also include density and viscosity of the sampled fluid. - In a laboratory environment (e.g., at the surface) fluid composition data can be analyzed up to hydrocarbon chains having 45 carbon atoms (C45), and sometimes longer chains. Other data in the fluid analysis reports that can be determined in a laboratory environment include gas-oil ratio (GOR) data, saturate aromatic resin asphaltene (SARA) analysis data, and flow assurance parameters such as, for example, asphaltene onset pressure, wax appearance/precipitation temperature (e.g., cloud point), and phase transition boundaries. Particular types of laboratories such as, for example, geochemistry laboratories can be used to perform relatively more specialized analyses including, for example, analysis of heavy metals, sulfurs, carbon isotopes, and crude oil fingerprinting. These specialized analyses can be used to investigate the origin of oil in a fluid and identify areas of reservoir compartmentalization (for example, geological segmentation of reservoirs into isolated compartments).
- In the illustrated example, the
example apparatus 300 is provided with apetrophysics simulator 310 to determine distributions of porosity, lithology and fluid content along the well 102 corresponding to the formation evaluation log data. In the illustrated example, thepetrophysics simulator 310 receives data from the formationevaluation logs database 304 to determine or simulate porosity, lithology, and fluid content data corresponding to the reservoir R based on the log information of the formation F and stored in the formationevaluation logs database 304. In some example implementations, the fluid content data determined by thepetrophysics simulator 310 represents a "black oil model" that includes coarse data indicative of proportions of water, oil and free gas without distinguishing between, for example, the type (e.g., the composition) of the oil. In the illustrated example, the DecisonXpress™ petrophysical evaluation system developed and sold by Schlumberger Technology Corporation can be used to implement thepetrophysics simulator 310. - To refine the description of the reservoir fluid determined by the petrophysics simulator 310 (e.g. C1, C2, C3-C5, C6+, and/or asphaltene concentrations) and, in particular, to determine the spatial distribution of the components of hydrocarbons, or other fluids, along the well, the
example apparatus 300 is provided with afluid simulator 312. In the illustrated example, the fluid analysis report data from the fluidanalysis report database 308 is communicated to thefluid simulator 312. In addition, the parameters used in thefluid simulator 312 to parameterize the variation of fluid composition within the individual flow units or segments of the well, may be used together with their associated uncertainties to perform comparisons between fluids in different flow units to determine how fluid properties or fluid characteristics change between the different flow units. - In some example implementations, the
fluid simulator 312 can be configured to determine an equation of state (EoS) from data stored in the fluid analysis reports. An EoS simulator determines an equation of state (e.g., the Peng-Robinson EoS) that relates oil composition, temperature, volume and pressure to represent the thermodynamic behavior of each fluid sample. The EoS can be used to compute fluid composition variations (e.g., concentrations of methane C1, the lumped group of hydrocarbons with 6 or more carbons C6+, asphaltene, etc.) in the flow unit, segment, or interval to which the fluid sample belongs. Typically, a flow unit is a rock or material volume in which the fluid may freely migrate. By segmenting each well (e.g., the well 102) according to the flow units through which it passes and determining at least one equation of state in each flow unit, thefluid simulator 312 can be used to determine hydrocarbon chain length distribution along the entire well. In the illustrated example, the PVT Pro™ EoS simulation tool developed and sold by Schlumberger Technology Corporation can be used to implement the fluid EoS simulator of thefluid simulator 312, or the PVTi™ EoS tool developed and sold by Schlumberger Technology Corporation can be used to implement thefluid simulator 312. - In yet other example implementations, one or more properties measured along the well 102 using in-situ fluid analysis sensors are stored in a
fluid analysis database 308 and are communicated to thefluid simulator 312. Thefluid simulator 312 determines (e.g. by surface fitting, by employing neural network techniques or other well known methods) a trend in the measured property(ies) and extrapolates this trend along each flow unit or segment of a well. - In the illustrated example, the
example apparatus 300 is provided with areservoir simulator 314 which generates fluid composition data for a distribution across an entire reservoir. Specifically, when fluid composition data is obtained (e.g. using thepetrophysics simulator 310 and/or the fluid simulator 312) along a plurality of wells in a reservoir, thereservoir simulator 314 can arrange the fluid composition data to generate a fluid composition distribution for that reservoir. In the illustrated example, thereservoir simulator 314 is configured to use the features of the geological model stored in the reservoirgeological model database 302 to populate the entire simulated reservoir in an empirical manner. That is, as the geological model data improves or more geological model data is acquired using, for example, fluid sample measurements or other types of measurements, thereservoir simulator 314 can update the fluid composition distribution or fluid map of the reservoir R. - The
reservoir simulator 314 may be a finite difference, a finite element, a finite volume or a streamline simulator that solves the equations governing the distribution of fluids and their fluid components at the scale of the reservoir R under constraints imposed by the fluid compositions measured along each well. In the illustrated example, the grid blocks of thereservoir simulator 314 should not be too coarse, but should instead be fine enough to capture the level of variation suitable for controlling drilling operations. The parameters (e.g. temperature gradient, capillary pressure curves, etc.) associated with equations governing the fluid distribution can be determined from prior knowledge (e.g., prior measurement data and/or analysis data of the reservoir R stored in, for example, the formationevaluation logs database 304, including, but not limited to, nuclear magnetic resonance and/or core data acquired in offset wells). Additionally, or alternatively, thepetrophysics simulator 310 can determine the water saturation profile across a water-oil contact in the reservoir R from the formation evaluations logsdatabase 304 and determine capillary pressure curves based on the water saturation profile data and sand face pressure measurements acquired with a sampling whiledrilling tool 142. In the illustrated example, the capillary pressure curves can in turn be used by thereservoir simulator 314 to determine water saturation levels away from the wellbore. In some example implementations, the ECLIPSE™ reservoir simulator tool developed and sold by Schlumberger Technology Corporation can be used to implement thereservoir simulator 314. - In some example implementations, an EoS determined by the
fluid simulator 312 may also be used to populate the fluid composition distribution over a simulated reservoir where the fluid is suspected to be in thermodynamic equilibrium and where the crude oil may be treated as a true molecular solution. - In other example implementations, stochastic processes conditioned to measurements made at key or select wells may be used to simulate a reservoir and populate the composition distribution over the simulated reservoir.
- In some example implementations, models of non equilibrium distributions of hydrocarbons can be used to analyze actual reservoir fluids and populate the composition distribution over the simulated reservoir. Non equilibrium distributions occur when reservoir fluids deviate from equilibrium, which can happen for different reasons. For example, reservoir fluids can deviate from equilibrium due to different factors including biodegradation, thermal gradients, current reservoir charging, charge history coupled with slow mixing kinetics, water/gas washing, leaky seals, and/or miscible floods. Typically, these factors can be modeled using an adjusted static model. In some instances, if one of the factors dominates the disequilibrium, that factor can be modeled with a simple parameter or set of parameters. For example, an empirical model can be used to find a linearly increasing contribution of biodegradation increasing towards an oil-water contact.
- In other example implementations, Archimedes buoyancy in Boltzmann equation shown in
equation 1 below can be used to populate the asphaltene concentration level over a reservoir and/or to determine the expected optical density (OD) in the visible range resulting from the asphaltene concentration level. For example, measurements may be conducted to detect asphaltene concentration levels in fluid samples and develop fluid models based on those asphaltene concentration levels. Asphaltenes are often present in crude oil as a nanocolloidal suspension, especially in highly under-saturated black oils. Asphaltene concentration is measurable using optical fluid analysis and, thus, one can determine if a black oil encountered is the expected black oil. That is, in drilling a new well, one can first predict and then perform measurements in real time to determine whether the black oil encountered in any flow unit or segment has the asphaltene content expected based on a fluid model of the reservoir previously developed using, for example,equation 1 below. - In
equation 1 above, OD(h) is the optical density or color of the oil at a height (h) induced by the asphaltene content, (V) is the volume of the asphaltene colloidal particle (found to be ~16Å for black oils), (Δρ) is the density contrast between asphaltene and the bulk oil, (g) is the Earth's gravitational constant, (k) is the Boltzmann's constant, and (T) is the temperature. For compressible oils, a semi-empirical methodology could alternatively be employed to describe the asphaltene concentration in those compressible oils. - In the illustrated example, the
example apparatus 300 is provided with a reservoirfluid map database 316 to store maps of fluid content (e.g., oil, water, gas) and the fluid composition maps of at least one of oil, water, or gas for subsequent use to determine well trajectories. For example, a reservoir fluid map data stored in the reservoirfluid map database 316 may be used when simulating production corresponding to two hypothetical production well trajectories. In such a case, the reservoir fluid map data is used to populate input data forprediction modules 315 including awell production simulator 318 and/or atool response simulator 320. In the illustrated examples described herein, the reservoir fluid maps can include data corresponding to portions of basin models generated using thereservoir simulator 314. A basin denotes a depression in the Earth's crust in which sediments accumulate. If hydrocarbon source rocks or material occur in combination with appropriate depth and duration of burial, then a petroleum system can develop within the basin. A basin model is a model that may account for the evolution of hydrocarbons from a source rock and their transformation with temperature and time, may model the migration and accumulation of hydrocarbons within the confines and structural features of the basin, and may allow the estimation of the associated uncertainty levels in the predictions of thereservoir simulator 314 across the geologic ages. Where reservoir fluid maps include basin simulated data, the reservoir fluid maps would represent the result of the simulated basin for the present days near the time frame during which measurements are acquired to determine well trajectories. A more detailed discussion of how thereservoir simulator 314 simulates basin data is presented below in connection withFIG. 3B . - As shown in
FIG. 3A , theexample apparatus 300 is provided with thewell production simulator 318 to predict a well's production by simulating a multiphase production flow in at least a portion of the reservoir surrounding a currently drilled well (e.g., the well 102 ofFIG. 1B ). For example, thewell production simulator 318 can utilize other data relating to relative permeabilities, end point saturations (e.g., bound water fraction), and capillary pressure curves determined by, for example, thepetrophysics simulator 310. In addition, thewell production simulator 318 can utilize formation pressure/temperature data, fluid mobility data acquired while sampling, drilling related information, mud filtrate invasion (see for example invadedzone 182 ofFIG. 1B ) data (which may be deduced from open-hole logs), and NMR data from the formationevaluation logs database 304. Thereservoir simulator 314 can use these properties in connection with the geological trends described by the geological model stored in the reservoirgeological model database 302 to generate a visual three-dimensional volume around the drilled well 102. Thus, thewell production simulator 318 can use the generated three-dimensional volume to predict how much hydrocarbon can be recovered for each hypothetical well trajectory, and the well trajectory to be formed by the drill string 104 (FIG. 1B ) can be selected based on the drainage of the reservoir R it provides. In the illustrated example, thewell production simulator 318 can be implemented using the SWPM™ (Single Well Predictive Modeling) tool developed and sold by Schlumberger Technology Corporation. - Alternatively or additionally, the fluid map data stored in the reservoir
fluid map database 316 can be used to predict a reservoir fluid log along the trajectory of a well. In this case, the fluid and geology map data from thereservoir map database 316 is communicated to thetool response simulator 320 that is configured to generate visual representations of the formation evaluation log data measured by the logging whiledrilling subsystem 126 and stored in the formationevaluation logs database 304 as the well 102 is being drilled. In the example implementations described herein, vertical well intersections are created along the well trajectory paths to create "well curtain sections" used to visualize the position of the well trajectory paths relative to seismic sections, faults, formation dips, marker beds, and/or other geologic features or properties of a reservoir. Thus, in the illustrated example, thetool response simulator 320 can determine predicted log data along a particular intersection with a well trajectory using composition information stored in the reservoirfluid map database 316. The predicted log data represents log data (e.g. optical spectroscopy absorbances in predetermined wavelength in the visible, near infrared range in the case of an optical spectrometer, mass spectra in the case of a mass spectrometer, or gas chromatography measurements) that would be acquired by fluid sensors (e.g., thespectrometer 204, a gas chromatographer, and/or thesensors 205 ofFIG. 2 ) implemented in a drilling system (e.g., theBHA 116 ofFIG. 1B ) if certain well trajectories were to be drilled. In this manner, an operator can select a particular well trajectory computed by thetool response simulator 320 showing predicted log data that the operator would like to achieve in actual measurements. Subsequently, during drilling operations to form or drill a selected well trajectory, the predicted log data can be compared to actual measurements collected using the downholemud logging tool 138 ofFIG. 1B or to the composition data of the pumped fluid measured using the sampling while drilling tool 142 (FIGS. 1B-3B ). The surface logging andcontrol system 120 can use the results of these comparisons to control the directional drilling subsystem 118 (FIG. 1B ) to adjust the trajectory of thewell 102. In the illustrated example, the Petrel™ tool developed and sold by Schlumberger Technology Corporation can be used to implement thetool response simulator 320. - In the illustrated example, the
example apparatus 300 is provided with or is coupled to the display/input interface unit 148 ofFIG 1B ,3A , and3B . The display/input interface unit 148 can be used to display to an operator the results of various operations based on the fluid map data, in conjunction with measurement data acquired by theBHA 116 and interpreted by thesurface system 120. Based on the displayed information, the operator may elect to select a particular well trajectory via the display/input interface unit 148. Theexample apparatus 300 is provided with atrajectory adjustment interface 324 to store the user-selected well trajectory in thewell trajectory database 306. In addition, thetrajectory adjustment interface 324 can apply the operator's selection in real time by communicating commands to theBHA 116 to achieve the selected trajectory. For example, thetrajectory adjustment interface 324 can communicate commands to thecommunications apparatus 128 of theBHA 116 to control the directional drilling subsystem 118 (FIGS. 1B and3A ) based on the selected well trajectory stored in thewell trajectory database 306. - In the illustrated example, the
BHA 116 is coupled to theexample apparatus 300. In this manner, real-time measurements performed by theLWD tool 126 and/or the sampling whiledrilling tool 142 and/or the mudgas logging tool 138 can be used to update the formationevaluation logs database 304 and/or the fluidanalysis reports database 308. In this manner, the data in the formationevaluation logs database 304 and/or the fluidanalysis reports database 308 can subsequently be used to determine new fluid maps as the well is being drilled. In addition, real-time measurements performed by theMWD tool 124 can be used to update the current well trajectory data in thewell trajectory database 306. -
FIG. 3B illustrates a portion of theexample apparatus 300 ofFIG. 3A to show how thereservoir simulator 314 can, among other things, be used to detect fluid compositional variation in a reservoir. The detected variations may in turn be accounted for in the reservoirgeological database 302 by inferring the occurrence of flow barriers (e.g. flow barrier 180 ofFIG. 1B ) or of reservoir charging (typically the history of an external flux of mass, such as gas or oil or even water in the reservoir). In the illustrated example, thereservoir simulator 314 simulates basin data. In some example implementations, the well 102 can be drilled along the reservoir R while monitoring the reservoir fluid properties to identify barriers to fluid flow. A barrier can be detected based on, for example but not exclusively, the detection of an abrupt change in the fluid pressure, the gas-oil ratio (GOR) or the color of the fluid within the reservoir R. Barrier detections can be confirmed using a vertical interference test or a drill stem test. - In the illustrated example, to detect fluid flows and barriers, the reservoir
geological model database 302 storesconnectivity model data 332 and chargingmodel data 334. In other example implementations, theconnectivity model data 332 and the chargingmodel data 334 can be stored on a different database. Theconnectivity model data 332 describes faults, possible flow passages, flow resistance, etc. in the reservoir R. The chargingmodel data 334 describes the source of downhole fluid (e.g., the components, the composition, flow direction, etc.). In some example implementations, theconnectivity model data 332 and the chargingmodel data 334 may be represented as a function of geological time. - In the illustrated example, the
reservoir simulator 314 uses theconnectivity model data 332 and the chargingmodel data 334 to predict the migration of the downhole fluids from one or more respective source rocks into other areas of the reservoir R and the change in the fluid composition data as a function of geological time. In addition, thereservoir simulator 314 can determine uncertainties for each of its predictions and store the predictions and their associated uncertainties corresponding to particular times (e.g., present time or future times) in thereservoir fluid map 316. - In operation, the data in the reservoir
fluid map database 316 may be communicated to thetool response simulator 320, which uses the data to predict what the sampling whiledrilling tool 142 would measure if certain wellbore trajectories were followed. After following (e.g., drilling or forming) a particular wellbore trajectory, the sampling while drilling tool 142 (or the mudgas logging tool 138, not shown) performs actual formation fluid measurements, and a chargingadjustment interface 336 and abarrier adjustment interface 338 can compare the actual measurements to the predicted data to determine whether to make adjustments to the chargingmodel data 334 or theconnectivity model data 332, respectively. For example, if the actual fluid sample measurements indicate inaccuracies in theconnectivity model data 332, then thebarrier adjustment interface 338 can adjust theconnectivity model data 332 to better conform to the actual fluid sample measurements. By adjusting theconnectivity model data 332 and the chargingmodel data 334 based on actual fluid measurement analyses, thereservoir simulator 314 can determine relatively more accurate reservoir fluid map data for the reservoirfluid map database 316. In this manner, theconnectivity model data 332 and/or the chargingmodel data 334 can be adjusted until the predictions generated by thetool response simulator 320 and the actual fluid sample measurements are in substantial agreement. Thus, the presence of a barrier can be detected when the data predicted by thetool response simulator 320 is not in substantial agreement with the actual fluid sample measurements. - If the charging
adjustment interface 336 and thebarrier adjustment interface 338 determine that the actual fluid sample measurements are in substantial agreement (i.e., within the uncertainty of the measurement) with the predicted data generated by thetool response simulator 320, then the confidence about the reservoir fluid map data in the reservoirfluid map database 316 increases and, thus, the uncertainties associated with the reservoir fluid map data may be reduced in the reservoirfluid map database 316. Thus, the presence of a barrier can be confirmed when the data predicted by thetool response simulator 320 is in substantial agreement with the actual fluid sample measurements. -
FIGS. 4A and4B depict a flowchart of an example method that may be implemented with theexample apparatus 300 ofFIG. 3A to control the well trajectory of a well (e.g., the well 102 ofFIG. 1B ). The example method ofFIGS. 4A and4B may be implemented using software and/or hardware. Although the example method is described with reference to the flowchart ofFIGS. 4A and4B , other methods may additionally or alternatively be used. For example, the order of execution of the blocks depicted in the flowchart ofFIGS. 4A and4B may be changed, and/or some of the blocks described may be rearranged, eliminated, or combined. - Turning to
FIG. 4A , initially, theexample apparatus 300 collects prior data about the reservoir R in which the well 102 is to be drilled (block 402), if available. Prior data may include a seismic cube of the reservoir R, logs of previous wells drilled in the reservoir, laboratory results for fluid samples or core samples obtained from the reservoir, etc. In the illustrated example, theexample apparatus 300 stores the prior data in the reservoirgeological model database 302, the formationevaluation logs database 304, and the fluidanalysis report database 308. If the prior data about the reservoir R is not available, measurements on a currently drilled well (e.g., the well 102 ofFIG. 1B ) can be performed to collect data about the reservoir R for the reservoirgeological model database 302, the formationevaluation logs database 304, and/or the fluidanalysis report database 308. - The reservoir simulator 314 (
FIG. 3A ) determines an initial reservoir fluid map from the prior data and determines an uncertainty map (block 404) of the reservoir R. The uncertainty map is used to indicate the uncertainties in the fluid property predictions in thewell 102. The initial fluid map may have a high level of uncertainty. However, using the example methods and apparatus described herein in a recursive manner while drilling a well enables collecting data to reduce the uncertainties as the well is drilled and, thus, may update the well trajectory in real time based on updates to the fluid map as the uncertainties are reduced. - The
well production simulator 318 or thetool response simulator 320 may be used by an operator to determine at least one initial well trajectory (block 406) based on, for example, the initial fluid map data determined atblock 404 and stored in the reservoirfluid map database 316. In some example implementations, an initial well trajectory is designed to enable new fluid measurements to be made to reduce the uncertainty of the reservoir fluid map determined atblock 404. In other example implementations, thewell production simulator 318 is used to determine an initial well trajectory atblock 406 that is designed to optimize hydrocarbon recovery from a reservoir. In yet other example implementations, thetool response simulator 320 can determine one or more well trajectories that are contingent on fluid measurements during the drilling of the well 102, and thetool response simulator 320 can be used to select one of the well trajectories atblock 406 as the initial well trajectory to optimize a particular objective (e.g., particular fluid measurement data). The drill string 104 (FIG. 1B ) is lowered in the well 102 (block 408), and drilling is started (block 410). - As described below, measurement data is collected by the
BHA 116, and the measurement data can be used in real time by theexample apparatus 300 ofFIG. 3A to update reports, models, and simulations in theexample apparatus 300. Measurement data can be collected before drilling, during drilling pauses, and/or after drilling the well 102 (e.g. while tripping out of the well). - In the illustrated example, the downhole mud
gas logging tool 138 acquires downhole mud gas logging data (block 412). In other example implementations, surface mud gas logging data may be used instead of downhole mud gas logging data, but the surface mud gas logging data may not be accurately indicative of the actual characteristics of the subsurface reservoir R. Mud gas logging data can be acquired during drilling without the need to stop or pause drilling. In the illustrated example, the mud gas logging data is used to derive information about the formation F being drilled and, more particularly, about the most volatile components contained in the formation fluid which are entrained in the drilling fluid as the formation rock is crushed by thedrill bit 106. The downhole mudgas logging tool 138 extracts these components from drilling mud in-situ and, more specifically, from drilling mud having formation fluid originating from within the formation F shortly after thedrill bit 106 passes a given depth. In this manner, the downhole mudgas logging tool 138 can analyze the flashed gas composition in, for example, a continuous fashion. After accounting for the background composition (e.g., the composition of the incoming drilling fluid 26 (FIG. 1B ) flowing from the drill bit 106), the change in the formation fluid composition introduced in thedrilling fluid 26 by the drilling process may be determined. - In some example implementations, the mud
gas logging tool 138 can monitor one or more molecular concentration(s) (e.g. methane concentration, ethane concentration, carbon dioxide concentration, concentration of a fluid injected in the reservoir etc...) extracted from the drilling mud samples after accounting for concentrations initially present in thedrilling fluid 26 leaving thedrill bit 106. In other example implementations, the mudgas logging tool 138 may also be used to monitor one or more concentration(s) of isotopes (e.g. the isotopes of carbon, 12C, 13C, etc...) associated with gases extracted from the drilling mud samples after accounting for concentrations initially present in thedrilling fluid 26 leaving thedrill bit 106. The monitored concentrations or other values derived therefrom are compared to corresponding log data predicted from the fluid map by thetool response simulator 320. In some cases, a discrepancy between measured data and predicted data greater than the measurement uncertainty may be indicative of compartmentalization that was not accounted for in the reservoir fluid model. In other cases, a discrepancy between measured data and predicted data greater than the measurement uncertainty may be indicative of the source of the methane, or carbon dioxide that was not accounted for in the reservoir fluid model. In yet other cases, a discrepancy between measured data and predicted data greater than the measurement uncertainty may be indicative of inaccurate composition gradients or inaccurate location of flood fronts in the fluid model. - In addition, the relative concentrations of the fluid constituents measured by the mud
gas logging tool 138 may be used to distinguish between fluids in the reservoir and/or to indicate, but not necessarily prove, the origin of the fluids. For example, carbon isotope measurements can be used to advantage for identifying the origin and maturity of hydrocarbons. Less definitively , the commonly used mud-gas logging wetness and balance ratios, respectivelyBernard ratio - In the illustrated example, the measurements made by the mud
gas logging tool 138 may be used to determine if a sidewall fluid sampling operation should be performed (block 414). In the illustrated example, thesurface system 120 uses the measurement information provided by the mudgas logging tool 138 and predicted information generated by thetool response simulator 320 to determine whether the fluid sampling operation should be performed. For example, a discrepancy between mud gas logging data measured by the mudgas logging tool 138 and predicted mud gas logging data generated by thetool response simulator 320 may be indicative of a flow barrier (e.g. flow barrier 180 ofFIG. 1B ) or a charging history improperly accounted for as the reservoir fluid map (stored in the reservoir fluid map database 316) has been determined. If such a discrepancy exists between the measured and the predicted mud gas logging data, asurface system 120 may cause the sampling whiledrilling tool 142 to extract and optionally to store one or more fluid samples from the formation and perform one or more fluid sample measurements. Thus, a sidewall fluid sampling operation may be performed if the mud gas logging data indicates that a significant change in fluid composition has occurred. Alternatively, a sidewall sampling operation may be scheduled at predetermined intervals or check points along the well trajectory such as, for example, close to expected gas-oil or oil-water contacts or other fluid transitions. In some example implementations, the operation ofblock 414 could be performed by an operator (e.g., an operator-performed decision) and the operator could provide user input based on the measurements made by the mudgas logging tool 138. For example, the computer 146 (FIG. 1B ) could display the mud gas logging data received from theBHA 116 and the predicted mud gas logging data generated by thetool response simulator 320 via the terminal display/input console 148 using a display or presentation configuration or arrangement that facilitates an operator-performed comparison of the data. - If a sidewall sampling operation is to be performed (block 414), the sampling while
drilling system 142 acquires sidewall sampling data (block 416). For example, the drilling operation of theBHA 116 is momentarily stopped and theprobe 144 of the sampling whiledrilling tool 142 is extended to engage the formation F. Thepump 202 is used to controllably draw fluid from the formation F. Fluid extraction continues until an acceptably low level of contamination (e.g., caused by seepage of thedrilling fluid 26 into the formation F) in the sampled stream is obtained. One of thesensors 205 in the sampling whiledrilling tool 142 measures formation fluid pressure and temperature, and thespectrometer 204 measures fluid spectroscopic data of the fluid sample. Coarse fluid composition data of the pristine formation fluid may be derived from the spectroscopic data, including partial concentrations such as methane concentration C1, ethane concentration C2, lumped concentration of propane, butanes and pentanes, C3-5, a lumped concentration of hydrocarbons having 6 or more carbon atoms in their molecules C6+, carbon dioxide concentration CO2. Also, GOR can be determined from the fluid composition, and asphaltene concentration may be derived from the optical density in the visible range measured using thespectrometer 204. In addition, water cut may be determined from spectroscopic data in the near infra-red range. Also, connate water acidity (pH), salinity (resistivity) can be determined. Finally, fluid mobility, fluid viscosity, and density may also be provided by analyzing the data obtained from one of thesensors 205. - The surface logging and
control system 120 and/or thedownhole electronics 208 compares the data derived from the measurements acquired during the sidewall sampling operation ofblock 416 with the mud gas logging data (acquired using the mud gas logging tool 138) (block 417). For example, the surface logging andcontrol system 120 can compare fluid composition data such as fluid component concentrations, or any other measurement data acquired during the sidewall sampling operation or data derived from the measurement data, such as uncertainty levels. - The surface logging and
control system 120 then determines whether it should adjust a calibration of the mud gas logging tool 138 (block 418). For example, the surface logging andcontrol system 120 can determine that it should adjust the mud gas logging calibration if the comparison between the sidewall sampling measurement and the mud gas logging data performed atblock 417 indicates that the mud gas logging data is not sufficiently in agreement with the sidewall sampling measurement within an acceptable measurement uncertainty. For example, the results of the mudgas logging tool 138 can be recalibrated based on the sidewall sampling measurements to provide an updated or relatively more accurate set of continuous fluid property logs along the well trajectory. In some example implementations, to compare the mud gas logging data to the sidewall sampling measurements, the surface logging andcontrol system 120 compares a subset of fluid composition components (e.g., C1-C8) acquired using the mudgas logging tool 138 to the same component concentrations measured during the sidewall sampling operation. Alternatively, the surfacelogging control system 120 can compare ratios of hydrocarbon concentrations acquired using the mudgas logging tool 138 to ratios of the same hydrocarbon concentrations acquired using the sidewall sampling operation. - If the surface logging and
control system 120 determines that it should adjust the mud gas logging calibration (block 418), the surface logging andcontrol system 120 adjusts the mud gas logging calibration (block 419). In the illustrated example, the surface logging andcontrol system 120 can adjust the mud gas logging calibration by updating fluid component ratios used as the calibration data. For example, if the calibration data includes a methane concentration calibration parameter and the mud gas logging measurement data indicates a methane concentration ratio of 60% while the sidewall sampling measurement indicates a methane concentration ratio of 50%, the calibration parameter corresponding to the methane concentration ratio can be adjusted until the mud gas logging measurement data indicates a methane concentration ratio of 50 % in agreement with the sidewall sampling measurement. Calibration data for other fluid components measured using the mudgas logging tool 138 can be adjusted in a similar manner. The surface logging andcontrol system 120 can store the mud gas logging calibration data in a memory in the mudgas logging tool 138 for subsequent use by the mudgas logging tool 138. - After the surface logging and
control system 120 adjusts the mud gas logging calibration (block 419) or if the surface logging andcontrol system 120 determines that it should not adjust the mud gas logging calibration data (block 418) or if a sidewall sample measurement is not performed (block 414), the surface logging andcontrol system 120 compares at least one of the measured fluid composition data (and its composition uncertainty) derived from the measurements acquired by the mudgas logging tool 138 atblock 412 and the measured fluid composition data (and its composition uncertainty) derived from the measurements acquired during the sidewall sampling operation ofblock 416 with the predicted and/or desired (or target) composition data (and its composition uncertainty) (block 420). For example, the surface logging andcontrol system 120 can compare fluid composition data, temperature, pressure, fluid component concentrations, or any other measurement data acquired or data derived from the measurement data. Measured composition data or other properties derived therefrom can be compared to a log predicted by the tool response simulator 320 (FIG. 3A ) based on the reservoir fluid map data in the reservoirfluid map database 316. - In some example implementations, the comparison operation of
block 420 could be performed by an operator (e.g., an operator-performed comparison) and the operator could provide user input based on the comparison (e.g., a decision to update the reservoir fluid map in the reservoirfluid map database 316 based on the comparison, etc.). For example, the computer 146 (FIG. 1B ) could receive from theBHA 116 the measured fluid composition data derived from the measurements acquired by the mudgas logging tool 138 atblock 412 and/or from the measurements acquired during the sidewall sampling operation ofblock 416. Thecomputer 146 could further display the received measured fluid composition data and a log predicted from the reservoir fluid map data via the terminal display/input console 148 using a presentation configuration or arrangement that facilitates an operator-performed comparison of the data. - The surface logging and
control system 120 determines whether to update the reservoir fluid map in the reservoir fluid map database 316 (block 421) (FIG. 4B ). For example, the surface logging andcontrol system 120 may determine whether to update the reservoir fluid map based on the comparisons between fluid composition measurements and prediction composition data performed atblock 420. In the illustrated example, the surface logging andcontrol system 120 can determine that it should update the reservoir fluid map when a discrepancy is observed between the sidewall sampling data and the measurement data predicted from the fluid map (e.g. a gas-oil contact is incorrectly located on the fluid map) and/or the mud gas logging data and the predicted measurement data. Whether discrepancies exist to warrant an update to the reservoir fluid map may be based on whether differences between the compared data indicate discrepancies that exceed an acceptable discrepancy threshold. The value or level of the discrepancy threshold may be directly related to the amount or magnitude of uncertainty in the measured and/or predicted composition data such that if the uncertainty is relatively large, the discrepancy threshold may be set to be more accepting of larger differences, whereas if the uncertainty is relatively small, the discrepancy threshold may be set to be less accepting of larger differences. When no discrepancies warranting an update of the fluid map are detected based on the comparisons, the surface logging andcontrol system 120 can elect not to update the reservoir fluid map. In instances in which an initial reservoir fluid map is not available, the surface logging andcontrol system 120 may determine atblock 421 to generate a reservoir fluid map when a sufficient amount of data has been collected by theBHA 116. - If the surface logging and
control system 120 determines that it should update the reservoir fluid map data, corrections can be made to the reservoir fluid map stored in the reservoirfluid map database 316. In the illustrated example, the fluid simulator 312 (FIG. 3A ) determines a new fluid EoS model using the downhole fluid composition analysis data generated by the mudgas logging tool 138 and/or the downhole fluid composition analysis data generated by the sidewall sampling tool 142 (block 422). Example methods that can be used to determine the new fluid EoS model are described inU.S. patent application serial no. 11/615,381, filed December 22, 2006 - Significant differences between the measured composition of the fluid and the fluid composition indicated by the fluid map (determined for example at block 420) can be indicative of erroneous predicted data (e.g., a horizontal composition gradient has been omitted from the data used to determine the predicted measurements) and/or one or more conditions in a reservoir. In the illustrated example of
FIGS. 4A and4B , the differences may be indicative of an inaccurate charging model (e.g., the chargingmodel data 334 ofFIG. 3B ) for the reservoir R and, thus, the chargingadjustment interface 336 determines a charging model for the reservoir R (block 424) by, for example, fitting a methane or carbon dioxide charging model to the measurements collected by the mudgas logging tool 138. Additionally or alternatively, the differences may be indicative of an inaccurate temperature charging model in the reservoir R, and the chargingadjustment interface 336 can fit a new temperature model to the temperature data points collected by the sampling whiledrilling tool 142 along the drilled well trajectory. - Another reason for the differences may be that an inaccurate
fluid connectivity model 332 was used for determining the reservoir fluid map of the reservoir R stored in the reservoirfluid map database 316. The inaccuracy may be detected from pH measurements in contiguous aquifers, or observed deviations of hydrocarbon compositions from composition gradients predicted using thermodynamic equilibrium (or an appropriate flux model if thermodynamic equilibrium is not indicated). In case such an inaccuracy is detected, thebarrier adjustment interface 338 can update the geological model data in the reservoirgeological model database 302 to reflect possible barriers to flow that cannot be detected with petrophysical logs, geologic logs, or seismic surveys. Thefluid connectivity model 332 may be iteratively altered or adjusted until the differences between the measured composition of the fluid and the fluid composition indicated by the fluid map are within the uncertainty of the measurements. The iterative adjustment may require modifying seal or fault positions or transmissibilities, which may be inferred from pressure data, LWD data such as resistivity imaging data, acoustic imaging data, pressure testing data and the like. - When the measured data matches the predicted data along the well 102, the
reservoir simulator 314 determines a new reservoir fluid map (block 426) by populating the fluid composition properties measured at the well over the reservoir R and the fluid composition uncertainty map in the reservoirfluid map database 316. In some cases, it may be found that ambiguities or discrepancies in the reservoir architecture need to be resolved to obtain a reservoir fluid map. - The
example apparatus 300 then determines whether it should adjust the well trajectory (block 428). For example, if the updated reservoir fluid map in the reservoirfluid map database 316 is significantly different from the reservoir fluid map used to plan the well, if an ambiguity or anomaly is detected in the reservoir architecture, or if a measured fluid property differs substantially from its predicted value, an operator may elect to adjust the well trajectory, as further described in connection withFIGS. 5 ,6 ,7 ,8 , and9 . - If an adjustment to the well trajectory is considered to be warranted (block 428), the new well trajectory may be determined by simulating one or more new well trajectory(ies) (block 430) and comparing the merit of one or more new well trajectory(ies) (block 432) to the current well trajectory in the
well trajectory database 306. For example, the display/input interface 148 can display the one or more new well trajectories in association with a current well trajectory to enable an operator to select one of the new well trajectories. The operations ofblocks FIG. 3A ) is used to implement the operations ofblocks well production simulator 318 can simulate the drainage/production corresponding to various well trajectories, and an operator can select the trajectory leading to the most economical value. Alternatively, the tool response simulator 320 (FIG. 3A ) can be used to simulate wells based on predicted fluid properties (e.g. fluid composition data), and a well trajectory can be selected by, for example, an operator based on a desired (or target) measured fluid property corresponding to the predicted fluid properties. The desired (or target) measured fluid properties may be associated with steering the well to follow fluid transition features or to avoid or stay away from other features (e.g., fluid contacts or tar mats). - After a well trajectory is selected (block 434), the display/input interface 148 (
FIGS. 1B ,3A , and3B ) updates the well trajectory in the well trajectory database 306 (block 436), and the surface logging and control system 120 (FIG. 1B ) communicates drilling direction commands to the directional drilling system 118 (FIGS. 1B and3A ) (block 438) to adjust the trajectory of the well 102 (FIG. 1B ). - The
example apparatus 300 then determines whether the drilling operation is finished (block 440). For example, the drilling operation may be finished if the well 102 is completed and drilling has reached a desired (or target) goal or objective (e.g., a desired drainage/production). Alternatively, the drilling operations may be finished if it is determined that no trajectory simulated by thewell production simulator 318 or the tool response simulator 320 (FIG. 3A ) achieves a desired goal, in which case drilling operations can be halted on a currently drilled well and another well may be started to try and achieve the desired goal. - If drilling operations have not finished (block 440), the
BHA 116 continues drilling according to the selected well trajectory (block 442) stored in thewell trajectory database 306, and control returns to block 412 ofFIG. 4A . However, if drilling operations have finished (block 440), the surface logging andcontrol system 120 instructs the platform andderrick assembly 100 to retrieve the drill string 104 (block 444) and, thus, theBHA 116. The surface logging andcontrol system 120 and/or thecomputer 146 can generate an operation report (block 446) and determine a well trajectory for a subsequent well (block 448). The example process ofFIGS. 4A and4B is then ended. - Although the example method of
FIGS. 4A and4B is described as being performed in real time while theBHA 116 is in the well and the well 102 is being drilled, in other example implementations, the example method can be performed in near real time. That is, the data collected during the drilling of the well 102 can be analyzed once theBHA 116 is brought to surface. In such example implementations, a reservoir fluid map can be created and/or updated as part of an operation report after the well 102 has been drilled. The operation report may also include laboratory analysis data of the samples drawn while drilling and a comparison of the laboratory analysis data and the real time in-situ measurement data. In some example implementations, the trajectory of the next well to be drilled in the reservoir R can be determined based on the reservoir fluid map as described above in connection withblocks FIG. 4A . - Although not shown, other reservoir information may also be updated while performing the example method of
FIGS. 4A and4B to, for example, generate the operation report atblock 446. For example, the updated data can include a reservoir fluid pressure map, a geology/lithology map, and a structural (fault, flow barriers) map. To update this data, other LWD deep measurements (e.g., deep azimuthal resistivity measurements, acoustic imaging measurements, formation testing while drilling measurements, etc.) could be performed by theBHA 116 and the results may be used to update the maps. -
FIGS. 5 ,6 ,7 ,8 , and9 are flowcharts of example methods that may be used to adjust well trajectories to achieve particular desired (or target) results associated with well drainage/production and/or to avoid or target particular structural features in a reservoir. The example methods ofFIGS. 5 ,6 ,7 ,8 , and9 may be implemented in combination withFIGS. 4A and4B . For example, the example methods ofFIGS. 5 ,6 ,7 ,8 , and9 may be implemented as variations of the example method ofFIGS. 4A and4B to implement respective processes. The example methods ofFIGS. 5 ,6 ,7 ,8 , and9 may be implemented using software and/or hardware. Although the example methods are described with reference to the flowcharts ofFIGS. 5 ,6 ,7 ,8 , and9 , the order of execution of the blocks depicted in the flowchart ofFIGS. 5 ,6 ,7 ,8 , and9 may be changed, and/or some of the blocks described may be rearranged, eliminated, or combined to achieve the same or similar results. - Turning to
FIG. 5 , an example method to determine whether to stop drilling operations based on real-time well production simulations involves predicting or estimating the production that can be achieved from an additional wellbore length yet to be drilled in a well (e.g., the well 102 ofFIG. 1B ). At some point during a drilling process the estimated production data for a subsequent wellbore length to be drilled may indicate a lower economical value (e.g., a low production, a production incompatible with the planned surface facility, etc.) than the cost of drilling the additional length. Thus, the drilling process can be stopped. - As shown in
FIG. 5 , initially one or more initial wellbore length(s) are drilled (block 502). The sampling while drilling tool 142 (FIGS. 1B-3B ) draws a formation fluid sample (block 504) and analyzes the fluid sample (block 506). For example, the sampling whiledrilling tool 142 can draw the formation fluid sample via theprobe 144 and analyze the fluid sample using thespectrometer 204 and/or the one or more additional sensor(s) 205 (FIG. 2 ). Alternatively, the mudgas logging tool 138 is used to capture a portion of the formation fluid present in thedrilling fluid 126 once the formation rock has been crushed (block 504) and analyses a flashed portion of the formation fluid (block 506). Preferably, but not necessarily, the sampling whiledrilling tool 142 and/or the mudgas logging tool 138 measures one or more of formation mobility, GOR, fluid composition, density, viscosity, pressure, and temperature. - The
reservoir simulator 314 updates the reservoir fluid map data stored in the reservoirfluid map database 316 ofFIG. 3A (block 508). In some example implementations, thereservoir simulator 314 adjusts the biodegradation gradient simulated for the reservoir R to match the fluid sample measurements. In other example implementations, thereservoir simulator 314 adjusts the thermal gradient simulated for the reservoir R to match the fluid sample measurement. In yet other example implementations, the fluid sample measurements acquired by the sampling whiledrilling tool 142 or the mudgas logging tool 138 may indicate that theBHA 116 has entered or is entering a new compartment in the reservoir R containing a different fluid and, thus, thereservoir simulator 314 adjusts the reservoir fluid map data in thedatabase 316 accordingly. - The well production simulator 318 (
FIG. 3A ) simulates the production of the well based on the already drilled wellbore lengths (block 510). In the illustrated example, thewell production simulator 318 simulates the production of the well based on the one or more wellbore lengths drilled atblock 502. Thewell production simulator 318 also simulates the production of the well 102 based on the wellbore length to be drilled (block 512). That is, thewell production simulator 318 simulates the production of the well 102 based on the one or more wellbore lengths drilled atblock 502 in combination with the wellbore length to be drilled. In some instances, thewell production simulator 318 may simulate production atblock 512 based on a plurality of possible wellbore lengths that may be drilled, each having a different trajectory to determine which trajectory of which length will have the most production. In this manner, thewell production simulator 318 may select the most promising wellbore length and trajectory with which to proceed to the operation ofblock 516. - The
well production simulator 318 then determines the production of the wellbore length to be drilled (block 516). In some instances, thewell production simulator 318 may determine that the production from the added wellbore length to be drilled is small due to, for example, the formation fluid being too viscous, the pressure being too low for the well to be economically produced, the formation F being of a poorer quality than had been anticipated, and/or elements in the fluid will rapidly precipitate and clog the part of the formation where the well 102 is to be drilled. Additionally or alternatively, thewell production simulator 318 may determine that the production from the added length will result in producing too much gas at the surface and that the production facilities which have to be constructed to handle the produced gas would be prohibitively costly. - The surface logging and
control system 120 then determines whether to continue drilling (block 518) the additional wellbore length. For example, the display/input interface 148 (FIGS. 1B ,3A and3B ) can receive input from an operator indicating whether to continue or stop drilling operations. If the surface logging andcontrol system 120 determines that drilling should continue (block 518), the surface logging andcontrol system 120 instructs theBHA 116 to drill the next wellbore length, and control is passed back to the operation ofblock 504. Otherwise, the surface logging andcontrol system 120 instructs the BHA 116 (FIG. 1B ) to stop drilling operations (block 522), and the platform andderrick assembly 100 retrieves the drill string 104 (block 524). The example process ofFIG. 5 is then ended. In some example implementations, the well 120 may be drilled further if, for example, other productive portions of the reservoir R may be reached by continuing to drill the well 120 even if the immediately subsequent length to be drilled is predicted to be uneconomical to produce. - Turning to
FIG. 6 , the depicted example method can be used to place a well in a reservoir containing injected fluid, such as gas. The example method may be used, for example, in instances in which new wells are drilled with the intent of recovering bypassed oil in a reservoir that has been under primary production or has been produced using injection. In the illustrated example, the example method is implemented to follow primary production by injecting gas which is miscible with the oil remaining in the reservoir R with the expectation that the oil recovery factor will increase. However, two typical concerns associated with the management of gas injection schemes include maintaining the gas pressure above a minimum miscibility pressure and knowing the position of the injection front throughout the reservoir R. Using the depicted example method ofFIG. 6 , the uncertainty in knowing the location of the injected gas front can be progressively reduced as new wells are drilled, thus improving the placement of current, sidetrack or future wells. To further reduce the uncertainty in knowing the location of the injected gas front, the pressure in the reservoir R may be monitored at various locations along newly drilled wells. - As shown in
FIG. 6 , initially, thereservoir simulator 314 may generate a reservoir fluid saturation map, that is representative of, amongst other things, the distribution of relative proportions of pristine formation fluid and/or injection fluid in the reservoir R (e.g. a saturation level of injected fluid) (block 602). In the illustrated example, thereservoir simulator 314 may generate at least a gas saturation map and additionally a pressure contour map, both of which reflect the incremental gas injection history and the oil production at the producing wells. Thetool response simulator 320 generates predicted fluid measurement log data for one or more well(s) to be drilled (block 604). Some of the predicted log data may correspond to anticipated fluid sampling log data based on the fluid saturation map generated atblock 602 at stations where in-situ fluid compositions are to be sampled. Other predicted log data may include a pressure profile along a well having pressures acquired at the same sampling station. Yet other predicted log data may correspond to possible gas breakthrough from a nearby injection well. - The sampling while drilling tool 142 (
FIGS. 1B-3B ) draws a formation fluid sample (block 606) and analyzes the fluid sample (block 608). For example, the sampling whiledrilling tool 142 can draw the formation fluid sample via theprobe 144 and analyze the fluid sample using thespectrometer 204 and/or the one or more additional sensor(s) 205 to determine fluid sample composition data, and in particular the relative proportions of pristine formation fluid and/or injection fluid in the fluid sample. Alternatively, the mudgas logging tool 138 may be used to analyze the composition formation fluid (e.g., analyze a concentration ratio between methane, or any other injected gas such as carbone dioxide, and another group of hydrocarbons such as embodied in the so called wetness ratio commonly used in mud gas logging). Preferably, but not necessarily, the measurements performed by the sampling whiledrilling tool 142 and/or the mudgas logging tool 138 include mass spectra measurements, gas chromatography measurements, optical reflectance measurements, optical absorbance spectra measurements in the near infra red range (e.g., at wavelengths characteristic of oil, methane and carbon dioxide), emulsion detection measurements from ultraviolet fluorescence, pressure measurements, temperature and fluid density measurements, and/or viscosity and mobility measurements. - Fluid sample composition data determined at
block 608 is then compared to the predicted and/or desired (or target) (e.g., sufficiently low) log data determined at block 604 (block 610). In the illustrated example, the comparison is used along with pressure measurements for a proposed well to determine if the pressure in the proposed well is sufficient for an injected gas to be miscible with in-situ oil and if the gas injection scheme is effective in contacting and mobilizing the remaining oil in the well formation F (FIG. 1B ). When the comparison ofblock 610 is performed for different points along the proposed well, each comparison may indicate a different result such that some portions of the proposed well have sufficient pressure while others may not. In the illustrated example, the comparison ofblock 610 will also indicate what changes should be made to reservoir fluid map data in the reservoirfluid map database 316 to reflect the latest data acquired atblock 608. - For each one of the well(s) to be drilled, the
reservoir simulator 314 updates respective formation evaluation logs in the formation evaluation logs database 304 (block 612) and geological logs in the reservoir geological model database 302 (block 614). In the illustrated example, theexample apparatus 300 also updates the pressure map in the reservoir fluid map database 316 (block 616) and the reservoir fluid saturation map in the reservoir fluid map database 316 (block 618). The updates ofblocks block 610 indicates no change in the formation evaluation model and the geological model, the formation evaluation model and the geological model need not be updated atblock - The
example apparatus 300 determines one or more possible wellbore length extension(s) that can be drilled in a current or one or more subsequent well(s) based on the updated reservoir fluid saturation map (block 620). For example, additional possible lengths may include lengths that steer the well 102 (FIG. 1B ) in a different direction or that continue drilling in the same direction to acquire additional information to make subsequent drilling decisions. For example, the additional information may be used to better understand the injection gas front of the reservoir R (FIG. 1B ) to plan a next well in the reservoir R. In the illustrated example, the example apparatus 300 (or an operator using the apparatus 300) may determine based on the comparison ofblock 610 that no subsequent lengths should be drilled and that the drilling of a current well should stop when, for example, the well in its current form may be used as a producer or as a gas injector. - In some example implementations, the operations of
block 610 and/or 620 could be performed by an operator (e.g., a database update decision based on the comparison, a well trajectory selection based on the comparison, etc.) and the operator could provide user input to theexample apparatus 300, based on a display or presentation configuration or arrangement that facilitates an operator-performed comparison of the data via the terminal display/input console 148. - Turning to
FIG. 7 , the depicted example method can be used to adjust well trajectories to plan a well in a compartmentalized reservoir. In the illustrated example ofFIG. 7 , potential compartmentalization in a reservoir is resolved during the drilling of the well, and the well trajectory can be modified based on an understanding of the fluid heterogeneity in the compartmentalized reservoir. Barriers to fluid flow in a compartmentalized reservoir are typically properties of the geological structures that contain the fluids. Barriers to fluid flow in rock structures often manifest themselves in measurable changes in fluid properties; for example, as a discontinuous change in some fluid parameter (e.g., parameters that can be measured using downhole fluid analysis (DFA) techniques include, a color parameter, a GOR parameter, an asphaltene content parameter, a CO2 content parameter, a gas composition parameter, a density parameter, a viscosity parameter, a pH parameter and a salinity parameter). In addition, flow barriers often manifest themselves by having higher density fluid in the oil column at locations which would violate static equilibrium. In the illustrated example described below, predicted data from a current geologic model is used to find flow barriers (e.g. flow barrier 180 ofFIG. 1B ). In addition, the example method ofFIG. 7 can be used to detect barriers or possible barriers based on measurement data acquired using other tools such as, for example, the PeriScope™ resistivity tool developed and sold by Schlumberger Technology Corporation. The example method ofFIG. 7 can be implemented using several DFA stations, each positioned on a different side of a potential barrier to detect fluid manifestations of barriers. - As shown in
FIG. 7 , initially thetool response simulator 320 generates predicted fluid measurement log data for a well (block 702). In the illustrated example, the predicted log data corresponds to fluid composition and/or fluid properties such as, for example, mass density and viscosity, typically in a sand shale sequence along a first trajectory. The sampling while drilling tool 142 (FIGS. 1B-3B ) draws a formation fluid sample (block 704) and analyzes the fluid sample (block 706). For example, the sampling whiledrilling tool 142 can draw the formation fluid sample via theprobe 144 and analyze the fluid sample using thespectrometer 204 and/or the one or more additional sensor(s) 205. Preferably, but not necessarily, the measurements acquired using the sampling whiledrilling tool 142 include fluid density and viscosity measurements, mass spectra measurements, gas chromatography measurements, and/or optical absorbance spectra measurements. Atblock 706 the sampling whiledrilling tool 142 and/or the surface logging and control system 120 (FIG. 1B ) can use the mass spectra, gas chromatography, and/or optical absorbance spectra measurements to determine, at least, the proportions of C1, C2, C3-5, C6+, CO2, H2O, and, in the case of optical absorbance, color, which can be used to determine the GOR and various ratios of combinations of the hydrocarbon components in the fluid sample. - The fluid sample measurements (and/or fluid composition) determined at
block 706 are compared to the predicted log data determined at block 702 (block 708). In addition, fluid compartmentalization is resolved (block 710) and the existence and locations of flow barriers (e.g. flow barrier 180 ofFIG. 1B ) in the reservoir are identified (block 712) based on the fluid compartmentalization. The operations ofblocks FIGS. 1B ,3A , and3B ). In other example implementations, the operations ofblocks - The
example apparatus 300 then adjusts the well trajectory (block 710) based on flow barriers identified at block 712 (block 714). For example, if fluid composition data or fluid property falls outside the predicted range determined atblock 702, a well trajectory may be adjusted to intersect a separate sand shale sequence to check the fluid contained therein. In some example implementations, different well trajectories contingent on fluid findings can be developed prior to beginning drilling operations of a well. The example process ofFIG. 7 is then ended. Although not shown, the process ofFIG. 7 can be repeated until a well is completely drilled or until a determination is made that drilling operations should no longer continue for the well. - In some example implementations using the example method of
FIG. 7 , other thermodynamic models based on first principles can be used to model the variations in concentration of asphaltenes and resins in a fluid. Asphaltenes and resins are the heaviest components of crude oil. Hydrocarbons could have minimal concentration variations of relatively lighter components and yet have an identifiable concentration variation of asphaltenes and or resins. Asphaltenes and resins dictate or influence the color of crude oil and can be measured in-situ by DFA techniques. Preferably, but not necessarily, under sampling conditions in which a fluid is pristine and no phase transitions have occurred, DFA measurement techniques can be used to achieve relatively more accurate measurement data of asphaltene-resin concentrations in a fluid. Variations in asphaltene and resin concentrations can be indicators of reservoir compartments. The large molecular aggregates of asphaltenes and resins are subject to buoyancy forces and, thus, anomalous changes in the natural distribution of these components within reservoirs are typically indicative of flow barriers. - Turning to
FIG. 8 , the depicted example method can be used to steer a well based on asphaltene precipitation onset pressure. In the illustrated example, the example method can be used to produce wells having relatively fewer flow assurance problems than might be achieved using other, traditional drilling techniques. The example method ofFIG. 8 uses characteristics such as, for example, fluid compositions represented by a reservoir fluid map to generate an asphaltene precipitation onset pressure map. In this manner, a well trajectory can be steered based on the precipitation onset pressure map. - As shown in
FIG. 8 , initially, the sampling while drilling tool 142 (FIGS. 1B-3B ) draws a formation fluid sample (block 802) and analyzes the fluid sample (block 804). For example, the sampling whiledrilling tool 142 can draw the formation fluid sample via theprobe 144 and analyze the fluid sample using thespectrometer 204 and/or the one or more additional sensor(s) 205. Preferably, but not necessarily, the measurements acquired using the sampling whiledrilling tool 142 include measures of optical absorption in the visible range and pressure measurements. Asphaltene typically causes an optical absorption that varies in the visible light range exponentially with the light frequency. Typically, asphaltene concentrations can be determined when gravity segregation and chemical equilibrium in the reservoir R are acting to generate or influence the presence of such asphaltene concentrations. Atblock 804, the sampling whiledrilling tool 142 and/or the surface logging and control system 120 (FIG. 1B ) correlate the color of the formation fluid to an asphaltene concentration in the fluid to refine the asphaltene concentration measure based on the formation fluid color. - The
reservoir simulator 314 then generates a reservoir fluid map (block 806) based on the asphaltene concentration. The reservoir fluid map can be determined by modeling how gravity segregation and chemical equilibrium affects variations in the concentrations of asphaltene at different subsurface depths. The fluid simulator 312 (FIG. 3A ) generates a precipitation onset pressure map (block 808) based on the reservoir fluid map generated atblock 806. In the illustrated example, thefluid simulator 312 generates the precipitation onset pressure map using an EoS equation. - The example apparatus 300 (or an operator) then compares the precipitation onset pressure map with production pressure in the well (block 810). For example, the precipitation onset pressure map generated at
block 808 can be compared to production pressures predicted by thewell production simulator 318 and pressure measurements acquired atblock 804. In some example implementations, the comparison operation ofblock 810 could be performed by an operator (e.g., an operator-performed comparison) and the operator could provide user input based on the comparison (e.g., a well trajectory selection based on the comparison, etc.). For example, the computer 146 (FIG. 1B ) could receive the precipitation onset pressure map from thefluid simulator 312 and production pressures from thewell production simulator 318 and display the at least a portion of precipitation onset pressure map and production pressures via the terminal display/input console 148 using a display or presentation configuration or arrangement that facilitates an operator-performed comparison of the data. - The
example apparatus 300 then adjusts the well trajectory based on the comparison (block 812). For example, the direction of drilling may be adjusted to avoid zones in the reservoir R that have a precipitation pressure that is too low. Thus, the well trajectory adjustment ofblock 812 may be made based on the comparison atblock 810 and a comparison of measured and predicted fluid properties that are computed from a fluid composition (e.g., precipitation onset pressure, equation of state (EoS), etc.). - For example, if a measured fluid composition indicates a precipitation onset pressure that is significantly different from a desired (or target) value, the well trajectory may be adjusted at
block 812 to avoid zones in the reservoir R that have a precipitation pressure that is too low and/or to achieve a well trajectory that will produce a desired (or target) fluid precipitation pressure along the drilled well. In some cases, drilling of a well may be stopped when it is determined that subsequent drilling will not achieve a desired (or target) or necessary precipitation pressure. - The
example apparatus 300 then determines whether the BHA 116 (FIG. 1B ) should continue drilling a current well (block 814). For example, theexample apparatus 300 may determine based on the comparison ofblock 810 that the drilling of the current well should be stopped if subsequent drilling will not achieve a desired or necessary precipitation pressure. Otherwise, if a well trajectory is selected atblock 812 that can avoid zones in the reservoir R that have a precipitation pressure that is too low, drilling may continue. If drilling is to continue, control is passed back to block 802. Otherwise, control passes to block 816, and theexample apparatus 300 is used to determine a well trajectory for a next well (block 816). In the illustrated example, a well trajectory for a side track well to be drilled in the same reservoir R may be determined based on the precipitation onset pressure map. The example process ofFIG. 8 is then ended. - Turning to
FIG. 9 , the depicted example method can be used to control the trajectory of a well (e.g., an almost horizontal well) to maintain the well trajectory below a gas-oil contact in an oil zone. The example method ofFIG. 9 can be advantageously used to determine relatively better well trajectories relative to gas-oil contacts than can be achieved using resistivity tools because gas-oil contacts do not offer a resistivity contrast. Also, in the case of light hydrocarbons having a transition to rich condensate gas, little or relatively low acoustical contrast between the oil zone and the gas zone exists. However, the example method ofFIG. 9 can be advantageously used to determine relatively better well trajectories relative to gas-oil contacts than can be achieved using acoustic tools. Where relatively large gradients in fluid properties exist, the example method ofFIG. 9 can be advantageously used to determine the gas-oil contact and adjust a well trajectory based on that gas-oil contact. - As shown in
FIG. 9 , initially, the sampling while drilling tool 142 (FIGS. 1B-3B ) draws a formation fluid sample (block 902) and analyzes the fluid sample (block 904). For example, the sampling whiledrilling tool 142 can draw the formation fluid sample via theprobe 144 and analyze the fluid sample using thespectrometer 204 and/or the one or more additional sensor(s) 205. Preferably, but not necessarily, the measurements acquired using the sampling whiledrilling tool 142 include GOR, C1, C2, C3-C5, and C6+ concentrations, and saturation pressure, i.e. bubble point/dew point pressure, measurements at reservoir temperature. Alternatively or additionally the mudgas logging tool 138 may be used to acquire composition data of the reservoir fluid. - The
reservoir simulator 314 then generates a reservoir fluid map (block 906) based on the measurements acquired atblock 904, including fluid composition data and/or saturation pressure predictions. In the illustrated example, to generate the reservoir fluid map, thefluid simulator 312 assumes that a chemical equilibrium exists in the reservoir R. Thefluid simulator 312 also determines or identifies the existence of a gas-oil (or water-oil) contact in the fluid map generated at block 906 (block 908). - The
example apparatus 300 then adjusts a well trajectory based on the determined contact (block 910). For example, theexample apparatus 300 may adjust the well trajectory to maintain the well in an oil zone at a desired (or target) distance from the gas-oil contact determined atblock 908. The well trajectory may be adjusted atblock 910 based on the contact identified atblock 908 by comparing a measured fluid property (e.g., a fluid composition and/or a saturation pressure) and a fluid property predicted in the fluid map. The point of the fluid map at which the measured and predicted properties match indicates a distance from a gas-oil contact. If the indicated distance is significantly different from a desired (or target) distance, the well trajectory may be adjusted to achieve a desired distance. The example process ofFIG. 9 is then ended. Although not shown, the process ofFIG. 9 can be repeated until a well is completely drilled or until a determination is made that drilling operations should no longer continue for the well. - In some example implementations, the comparison operation of
block 910 could be performed by an operator (e.g., an operator-performed comparison) and the operator could provide user input based on the comparison (e.g., a well trajectory selection based on the comparison). For example, the computer 146 (FIG. 1B ) could receive fluid properties (e.g., a fluid composition and/or a saturation pressure) measured along the well trajectory from theBHA 116 and display the received fluid properties on the reservoir fluid map via the terminal display/input console 148 using a presentation configuration or arrangement that facilitates an operator-performed comparison of theBHA 116 location and gas-oil contact location. - In some example implementations, the example methods of
FIG. 9 can also be used to adjust or steer well trajectories relative to an oil-water contact or to maintain a position relative to biomarkers or the quality of an oil body where the quality is, for example, a measure of the degree of biodegradation that has taken place. In such example implementations, measurements acquired using the sampling whiledrilling tool 142 atblock 904 include measurements of benzene and toluene in the case of the oil-water contacts, fluid composition measurements up to at least C30 in the case of biodegradation, and/or carbon and hydrogen isotopic ratio measurements. To determine fluid composition data based on biodegradation, the sampling whiledrilling tool 142 can alternatively be used to measure in-situ density, GOR, gas gravity, and viscosity, and the degree of biodegradation may be inferred from local correlations of such measurements. - Although certain methods, apparatus, and articles of manufacture have been described herein, the scope of coverage of this patent is not limited thereto. To the contrary, this patent covers all methods, apparatus, and articles of manufacture fairly falling within the scope of the appended claims.
Claims (15)
- A method to form a well, comprising:determining, based on prior data, a fluid map associated with at least a portion of a reservoir, the fluid map having first fluid composition data associated therewith; andmeasuring a formation fluid parameter;determining second fluid composition data based on the measured parameter;comparing the second fluid composition data with the first fluid composition data associated with the fluid map; the method characterised bydetermining a fluid property uncertainty map associated with at least the portion of the reservoir;determining an uncertainty associated with the second fluid composition data;comparing the uncertainty associated with the second fluid composition data with the fluid property uncertainty map associated with the portion of the reservoir; andadjusting a well trajectory based on:the comparison of the second fluid composition data with the first fluid composition data associated with the fluid map; andthe comparison of the uncertainty associated with the second fluid composition data with the fluid property uncertainty map associated with the portion of the reservoir.
- A method as defined in claim 1, further comprising:conveying at least one sensor into a borehole;wherein measuring the formation fluid parameter comprises measuring in situ using the sensor positioned in the borehole.
- A method as defined in claim 1, wherein the second fluid composition data includes a hydrocarbon content or an asphaltene content.
- A method as defined in claim 1, further comprising:updating the fluid map based on the comparison; andreducing an uncertainty associated with the updated fluid map;
- A method as defined in claim 1, further comprising:updating at least one of formation evaluation log data, geological log data, or pressure map data; andupdating the fluid map based on at least one of the updated formation evaluation log data, the updated geological log data, or the updated pressure map data.
- A method as defined in claim 1, further comprising identifying a fluid contact on the fluid map and adjusting the well trajectory relative to the fluid contact indentified on the fluid map.
- A method as defined in claim 1, wherein the second fluid composition data determined from the fluid measurement and the first fluid composition data associated with the fluid map comprise injection fluid saturations.
- A method as defined in claim 1, wherein the second fluid composition data comprises a concentration of at least one component of the measured fluid and wherein the at least one component includes a molecular component.
- A drilling system comprising:a processor; anda machine accessible medium coupled to the processor and having instructions stored thereon that, when executed, cause the drilling system to:determine, based on prior data, a fluid map associated with at least a portion of a reservoir;measure a formation fluid parameter; anddetermine fluid composition data based on the measured parameter; the machine accessible medium characterised in that the instructions, when executed, also cause the drilling system to:receive a well trajectory selection associated with a comparison of the fluid composition data with the fluid map;determine a fluid property uncertainty map associated with at least the portion of the reservoir;determine an uncertainty associated with the fluid composition data; andadjust a well trajectory based on the well trajectory selection and a comparison of the uncertainty associated with the fluid composition data with the fluid property uncertainty map associated with the portion of the reservoir.
- A drilling system as defined in claim 9, wherein the instructions, when executed, cause the drilling system to perform the comparison of the fluid composition data with the fluid map.
- A drilling system as defined in claim 9, wherein the instructions, when executed, cause the drilling system to:display the fluid composition data and the fluid map; andreceive a user input indicative of the well trajectory selection.
- A drilling system as defined in claim 9, wherein the instructions, when executed, cause the drilling system to update the fluid map based on the comparison of the fluid composition data with the fluid map.
- A drilling system as defined in claim 9, wherein the instructions, when executed, cause the drilling system to reduce an uncertainty associated with the fluid map based on the comparison of the fluid composition data with the fluid map.
- A drilling system as defined in claim 9, wherein the instructions, when executed, cause the drilling system to update at least one of formation evaluation log data, geological log data, or pressure map data.
- A drilling system as defined in claim 9 further comprising:a sensor to measure a formation fluid; anda directional drilling subsystem.
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EP15175548.5A EP2966257A1 (en) | 2008-05-22 | 2009-04-14 | Method and system to form a well |
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US12/125,181 US8061444B2 (en) | 2008-05-22 | 2008-05-22 | Methods and apparatus to form a well |
PCT/US2009/040519 WO2009142840A2 (en) | 2008-05-22 | 2009-04-14 | Methods and apparatus to form a well |
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EP15175548.5A Withdrawn EP2966257A1 (en) | 2008-05-22 | 2009-04-14 | Method and system to form a well |
EP09751070.5A Not-in-force EP2315914B1 (en) | 2008-05-22 | 2009-04-14 | Methods and apparatus to form a well |
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WO2009142840A3 (en) | 2010-01-14 |
EP2315914A2 (en) | 2011-05-04 |
US8061444B2 (en) | 2011-11-22 |
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